172 results about "Quality management" patented technology

The invention discloses a material batch full-process traceability system based on a production process, particularly relates to the field of production and manufacturing traceability, is used for solving the problems of continuity and accuracy of material batch full-process traceability, and is characterized in that batch tracking coordinates are generated by constructing a process mapping matrix and an assembly topological index; detecting circulation holes in real time and inserting placeholder marks; judging broken chain credibility based on path integrity and structural complexity; compressing traceable chain segments; executing field dynamic alignment to generate batch circulation patches; a material batch whole-process continuous tracing view is established; and furthermore, the abnormity positioning time is remarkably shortened, the real-time performance is improved, the influenced batches are accurately locked, the recall range is reduced, the production line decision-making efficiency is optimized, and efficient and reliable technical support is provided for quality management and batch tracking in the production process.

The invention discloses a flexible automatic production management and control system for a new energy high-power high-frequency transformer, and relates to the field of production management and control, the flexible automatic production management and control system comprises a production demand receiving module, a production resource management module, a production planning module, a production execution module and a quality control module, an order is received through an API or EDI, and a work order is generated; collecting equipment and material information in real time, and constructing a production resource association network; carrying out production scheduling and process matching by adopting an improved deep learning model; scheduling materials, procedures and equipment based on a multi-level analysis control model; the quality is evaluated by using a two-dimensional cloud model, and data recording is performed through a distributed database, so that the traceability of the quality problem is ensured. According to the system, the production efficiency and the quality management level are effectively improved, the problem that existing rigid automatic equipment lacks flexibility is solved, and efficient and accurate production of the new energy high-power high-frequency transformer is ensured through cooperative work of a plurality of modules so as to meet different production requirements.

A multi-tenant, cloud-based Software-as-a-Service (SaaS) manufacturing cloud system offers a variety of industrial applications to end customers, including but not limited to MES, ERP, quality management, supply chain management, and customer relationship management (CRM). The system includes extensibility tools that allows industrial customers to customize databases, data collection templates, reporting fields, and other features of their consumed services, eliminating the need for these features to be customized by an administrator of the cloud system. Some embodiments of the manufacturing cloud system can also leverage generative artificial intelligence (AI) in connection with executing its supported services.

The invention relates to the technical field of computers, discloses a product full-process quality monitoring method and system based on big data, and aims to solve the problem of insufficient quality management refinement caused by data islands, monitoring lag, tracing difficulty and single analysis dimension in the prior art. The method comprises the following steps: constructing a full-process data acquisition system covering design, materials, production, logistics and after-sale, integrating multi-source heterogeneous data, and performing cleaning and time alignment; using an LSTM and GRU mixed model to extract time sequence features of the process parameters, and generating a high-dimensional process feature vector; and constructing a material-process-quality association knowledge graph in combination with the graph attention network, and representing the internal association of the quality influence factors of each link. According to the scheme, full-process data fusion, active quality prediction, accurate traceability and intelligent optimization are realized, and the real-time performance, the accuracy and the self-adaptive capability of quality control are remarkably improved.

The invention discloses a supply chain quality collaboration method and system based on a block chain, and relates to the technical field of block chain and supply chain quality management, and the method comprises the steps: collecting quality events according to a batch quality collaboration baseline table, generating a credible collection proof package and a to-be-verified quality event queue, executing dynamic endorsement verification, and writing the dynamic endorsement verification into a quality event account book, outputting a batch state table and an under-chain evidence pointer; performing rapid detection and judgment based on the batch state table and the under-chain evidence pointer, generating a pre-release report and establishing a pre-release mapping table; and triggering a difference correction contract according to the pre-release mapping table, updating the batch state table, generating a collaborative work order, pushing a quality collaborative strategy instruction, and outputting a quality collaborative closed-loop record. According to the method, the risk feedback analysis result table is generated by auditing and evaluating the quality collaborative closed-loop record, the risk layering strategy table is revised, and the batch quality collaborative baseline table is updated, so that the key field constraint is continuously calibrated, and the traceability and consistency of collaborative processing are improved.

A multi-tenant, cloud-based Software-as-a-Service (SaaS) manufacturing cloud system offers a variety of industrial applications to end customers, including but not limited to MES, ERP, quality management, supply chain management, and customer relationship management (CRM). The system includes extensibility tools that allows industrial customers to customize databases, data collection templates, reporting fields, and other features of their consumed services, eliminating the need for these features to be customized by an administrator of the cloud system. Some embodiments of the manufacturing cloud system can also leverage generative artificial intelligence (AI) in connection with executing its supported services.

The present invention relates to the field of intelligent manufacturing and discloses a PCBA product quality management and optimization system and a data transmission method to achieve secure storage and targeted sharing of quality management data. The method includes: a cloud server receives and parses a request sent by a client, performs a hash calculation based on the parsed information of the request, and searches the cloud storage resources for ciphertext data A with the hash calculation result as the file name; if so, when forwarding the request to an edge server deployed locally on the requested party, the request is accompanied by a mark indicating that the target quality management data has been uploaded to the cloud; the ciphertext data A is then sent to the edge server; after receiving the request, the edge server performs waiting processing on the ciphertext data A according to the mark information, and after receiving the ciphertext data A, the ciphertext data A is decrypted and then encrypted with the public key of the requested party to obtain ciphertext data B, which is then forwarded to the client via the cloud server to finally decrypt and output the target quality management data.

The invention relates to a titanium alloy smelting quality management method and system. The method comprises the steps that real-time monitoring data in the titanium alloy smelting process are collected; classifying and storing the real-time monitoring data to obtain historical process data; performing equipment abnormity early warning based on the equipment operation data and a preset first early warning rule, and generating first early warning information; obtaining a process capability index based on the process control node data, performing process data deviation early warning based on the obtained process capability index and a preset second early warning rule, and generating second early warning information; performing product manufacturing and detection early warning based on the ingot casting product manufacturing and detection data and a preset third early warning rule, and generating third early warning information; and displaying and processing the first early warning information, the second early warning information and the third early warning information in a man-machine interaction mode. Effective guidance is provided for quality management of titanium alloy smelting, and potential problems can be found and eliminated in time.

A multi-tenant, cloud-based Software-as-a-Service (SaaS) manufacturing cloud system offers a variety of industrial applications to end customers, including but not limited to MES, ERP, quality management, supply chain management, and customer relationship management (CRM). The system includes extensibility tools that allows industrial customers to customize databases, data collection templates, reporting fields, and other features of their consumed services, eliminating the need for these features to be customized by an administrator of the cloud system. Some embodiments of the manufacturing cloud system can also leverage generative artificial intelligence (AI) in connection with executing its supported services.

The invention discloses an intelligent project implementation management system and method based on multi-source perception fusion, and aims to solve the problems of information isolated island, response lag, experience dependence, extensive management and control and the like in an engineering project. According to the system, multi-source data acquisition is carried out through an Internet of Things sensor, a video monitor, a mobile terminal, a BIM / GIS, a project management platform and the like, and after space-time alignment and standardization processing are carried out, a unified situation awareness view is constructed by adopting a hierarchical fusion strategy; performing real-time intelligent evaluation and prediction on progress, quality, safety, cost and resources based on the fused data; a rectification, scheduling or early warning instruction is automatically generated, and a sensing-analysis-decision-execution closed loop is realized by pushing and linking a field execution system through multiple channels; according to the method, the safety prevention and control, quality control and progress performance capabilities are remarkably improved, the accident rate and cost are reduced, and project management is promoted to be transformed and upgraded to a refined, active and self-evolution direction.

The invention relates to the technical field of gas appliance quality control, and discloses a quality data analysis management system based on gas appliance production and after-sales service. A data acquisition module of the system acquires a process parameter time sequence from a distributed production terminal, and acquires a running state alarm event flow from a user service terminal in real time; the feature analysis module performs abnormal fluctuation compensation on a process parameter time sequence in a quality information fusion analysis mode, generates a multi-dimensional quality defect feature spectrum and determines a process tracing period; the risk conduction module obtains part circulation path information and analyzes defect correlation characteristics to obtain quality coupling data, and the production batch quality safety situation level is determined in combination with an alarm event flow; and the regulation and control execution module intervenes the full-life-cycle dynamic quality management and control blind area according to the process tracing cycle and the quality safety situation level. The system realizes integrated management of production and after-sales service quality data, and improves the effectiveness of quality management and control.

The invention discloses a product image-text and document association identifier generation method fusing a PLM coding rule, relates to the technical field of product data management, and is used for solving the problem that an image-text and document association identifier is not clear. According to the method, document information vectors are constructed by fusing PLM coding rules and collecting document metadata of design drawings, process documents, quality management and bill-of-material systems, an image-text document structure mapping chain is generated through a structure mapping judgment model, a unique association identifier of the image-text document is generated in combination with a preset template, and the unique association identifier of the image-text document is obtained. And real-time updating is carried out during structure replacement, hierarchical reconstruction or configuration change, cross-system serial number semantic alignment is realized through a heterogeneous coding analysis rule base, heterogeneous naming conflicts are solved, identifiers are written into a product data management platform, an index relationship is established, hierarchical retrieval, version switching and historical backtracking are supported, and the product data management efficiency is improved. And the consistency and cooperation efficiency of product research and development and quality control are improved.

The invention relates to industrial data management, more particularly belongs to the technical field of industrial internet, and particularly relates to a construction quality management method and system based on a digital power plant, and the method comprises the steps: defining a construction quality acceptance threshold value of the power plant through analyzing a defect generation mode of the power plant in a construction process; determining a key process control period when the power plant reaches a quality acceptance threshold according to the constructed power plant adaptive quality control list; simulating a construction process of executing the self-adaptive quality control list by the power plant, and recording controllable process parameters in the simulation process; establishing a construction quality risk cloud picture of the power plant, and calculating a defect evolution rate corresponding to the construction quality risk cloud picture; and according to the defect evolution rate, generating a dynamic parameter regulation and control strategy set of the adaptive quality management and control list to output a construction quality management result of the power plant. According to the invention, accurate control of construction quality management can be realized, and the construction quality and safety of a power plant are guaranteed.

The invention provides a digital production management system and a method thereof. The digital production management system comprises a manufacturing operation management subsystem and a plurality of user mobile terminals, the manufacturing operation management subsystem comprises a plan management module which is used for managing production orders and delivery notices; the production management module is used for managing the work order and managing production data uploaded by the user mobile terminal in the production process; the production configuration management module is used for managing and configuring production basic data; the quality management module is used for setting and managing quality inspection standards, managing the quality process of the work order and managing quality data uploaded by the user mobile terminal in the production process; the warehouse management module is used for managing a delivery plan, a receiving notice and a return notice, and managing warehouse data uploaded by the user mobile terminal in the production process; and the user mobile terminal is used for inputting production data, quality data and warehouse data and feeding back the production data, the quality data and the warehouse data to the manufacturing operation management subsystem and / or the ERP system.

The invention relates to the technical field of metal industry chain quality management, and discloses a key metal industry chain quality collaborative improvement method based on a quality atlas, and the method comprises the steps: collecting local quality data of each enterprise of a metal industry chain, and carrying out the preprocessing; extracting quality knowledge based on the standardized data set to preliminarily construct a quality map, and fusing and complementing the quality map; mining quality influence factor association; carrying out quality abnormity intelligent diagnosis by fusing statistical detection and map reasoning; constructing a digital twinborn simulation model, and carrying out collaborative optimization on each link of an industrial chain by adopting a hierarchical decision framework; the industrial chain quality collaborative optimization scheme is executed in stages, continuous monitoring feedback is carried out, and an optimization implementation effect report is obtained; according to the invention, through construction of the quality map covering the whole industrial chain and intelligent correlation analysis, key factors influencing the quality of the terminal product can be accurately identified, and accurate quality control is realized.

The invention discloses an automobile aluminum ornament product quality inspection method based on big data, particularly relates to the field of quality management and quality inspection decision, and is used for solving the problem that existing aluminum ornament quality inspection depends on fixed rules and experience judgment and is difficult to dynamically optimize quality inspection performance and resource allocation in combination with after-sales quality information. According to the method, structured processing and damage mode division are performed on vehicle after-sales damage data, key process features are extracted in combination with production process time sequence data, and a defect early propagation model is constructed, so that prediction of occurrence probabilities of different defect types is realized; on the basis, a multi-layer hierarchical quality inspection strategy is dynamically generated according to the defect risk level, quality inspection execution cost and historical quality loss cost are integrated, and quality inspection performance indexes of a next production cycle are output through multi-objective optimization, so that the scientificity and decision value of quality risk management are improved while the cost is controlled, and the quality risk management efficiency is improved. Therefore, the management requirements of refined operation and cost constraint are met.

The invention relates to the technical field of quality management, in particular to a stamping hardware quality management method and system. Obtaining input production batch information and production event context information; acquiring quality data uploaded by the automatic detection equipment and associated detection context information, wherein the detection context information comprises detection time, a detection equipment identifier and a batch identifier; performing multi-dimensional consistency evaluation based on the production batch information, the production event context information and the detection context information; according to a result of the multi-dimensional consistency evaluation, performing association judgment and establishing an association relationship between the quality data and the production batch information; and marking the quality data which cannot establish the association relationship through association judgment, and prompting workers to check. The technical problem that in large-scale production of stamped hardware, due to the fact that batch information input is inconsistent or wrong, association between quality data and actual production batches is disordered is solved.

The invention provides a mechanism special for full-automatic positioning of MINILED products, and relates to the technical field of LED product production and machining. The first width adjusting module is arranged on the rack and used for adjusting and positioning the product in the first direction; the second width adjusting module is arranged on the rack and used for adjusting and positioning the product in the second direction, and the second direction is perpendicular to the first direction; and the lifting table is arranged on the rack in a lifting mode through a lifting hydraulic cylinder, and the lifting table is located between the first positioning edge mechanism and the third positioning edge mechanism and located between the second positioning edge mechanism and the fourth positioning edge mechanism. High-automation and intelligent production is achieved, the production flexibility and the production changing efficiency are improved, the information tracing function is integrated, quality management is enabled, positioning is accurate and reliable, the machining quality is guaranteed, the structural design is compact and reasonable, and universality is high.

The invention relates to the technical field of manufacturing traceability, in particular to a product traceability method and system for an automatic laminating machine, and the method comprises the following steps: obtaining a head direction and state change, extracting a path direction and a code, recognizing a change node, judging a connection relation, connecting a path, and associating a task with a path number. And analyzing interval and station change, adding serial numbers, and writing task data to generate fitting process traceability chain content. According to the method, through dynamic data acquisition and analysis and whole-process monitoring and automatic recording of the fitting process, the real-time performance and integrity of data are improved, positioning of track change nodes and connection of path segments are achieved, state changes of each stage are kept to be captured in time, the states of the path segments and the stations are intelligently analyzed, linkage between links is optimized, and the efficiency is improved. The execution continuity is improved, human intervention and errors are reduced, the traceability from the task source to the execution process is enhanced, and the transparency and controllability of product quality management are improved.

The invention provides a self-adaptive data quality rule threshold dynamic generation system, belongs to the technical field of data management in communication operator data, and aims to solve the problem that a threshold for configuring an audit object table in a communication operator data quality module depends on artificial experience and is difficult to adapt to service changes in time. A three-layer architecture system of an auditing feature analysis layer, a rule generation modeling layer and a dynamic optimization layer is innovatively constructed. According to the method, historical data of an auditing object table are analyzed, and an lsolation Forest isolation forest algorithm is adopted, so that a dynamic quality threshold adaptive to business scene changes is automatically generated. According to the scheme, the auditing rule accuracy can be effectively improved, the manual intervention frequency of rule maintenance is reduced, and automatic operation of quality management and control of a data intermediate station is effectively supported.

The embodiment of the invention provides a data management method and system for a product production process, equipment, a medium and a product, and the method comprises the steps: arranging a production process flow for a to-be-produced product model, the production process flow comprises at least one production process, and each production process corresponds to a unique process identification number; in the production process according to the production process flow, creating a product instance of the product model, the product instance corresponding to a unique product instance identification number; and obtaining production log data corresponding to each production process of the product instance, associating the production log data corresponding to the production process with the corresponding process identification number and the product instance identification number, and storing the production log data in the cloud. By using the method, the production log data generated by each process can be automatically stored in the cloud, and by establishing a complete product production process log recording and tracing system, the integration and sharing of the production data are realized, the information island phenomenon is avoided, and the production efficiency and the quality management level are improved.

The invention relates to the technical field of quality management traceability, and particularly discloses an aromatic beverage production quality traceability and process intelligent management system, which comprises an initialization module for acquiring spectral data of raw materials, extracting raw material characteristic data based on the spectral data and generating initial packaging parameters; the real-time acquisition module is used for acquiring filling procedure parameters, sealing procedure parameters and environment control parameters in real time in the beverage production process; the optimization module is used for inputting the collected filling procedure parameters, the collected sealing procedure parameters and the collected environment control parameters into a decoupling algorithm to obtain mutually independent characteristic parameters; calculating a parameter adjustment amount through an optimization algorithm based on the difference between the feature parameter and a preset target parameter; and the control module is used for updating equipment control parameters according to the parameter adjustment quantity and executing corresponding equipment adjustment operation. The method can play a significant role in improving the product stability, enhancing the process control capability and perfecting the quality traceability.

The application discloses a demand traceability method based on an OSLC standard, and comprises the following steps: step S1, developing a demand software adapter; step S2, developing a modeling software adapter; step S3, designing a client application to acquire and display data; step S4, establishing a traceability relationship between demands and models; step S5, realizing query and visual display of the traceability relationship; and step S6, realizing demand change influence analysis. The application fully utilizes the OSLC standard, realizes seamless integration of heterogeneous tools without large-scale modification through data standardization of demand software and modeling software, greatly improves the universality and interoperability between tools, effectively reduces implementation cost, provides bidirectional traceability capability between demands and models, ensures demand integrity and model consistency, and significantly improves the quality management capability in a system development process.

The invention provides a quality performance evaluation method and device, electronic equipment, a medium and a program product, and relates to the technical field of computers. The quality performance evaluation method comprises the steps that fusion processing is carried out on different types of quality related data collected from a multi-source heterogeneous data system to obtain multi-dimensional quality fusion data, and the quality related data represents data related to quality management; quantitative characteristics of the quality performance are obtained; an evaluation model which is adaptive to the quantitative characteristics and has multi-dimensional quality performance indexes is constructed based on the domain requirements and the business scenes, and the evaluation model determines the weights of the performance indexes based on an analytic hierarchy process; and inputting the quantitative characteristics of the quality performance into the evaluation model to obtain a quality performance evaluation result. Through the technical scheme disclosed by the invention, dominant indexes and potential association rules of all links of quality management are comprehensively captured, so that the objectivity, accuracy and systematicness of evaluation results are improved.

The invention relates to the field of equipment production, in particular to a quality threshold constraint-based construction period control method and system. According to the quality threshold constraint-based construction period control method and system provided by the invention, quality attenuation modeling is carried out by fusing factors such as production fluctuation perception, quantified overtime, delay and the like which capture order demand change and production resource state change in real time, the construction period, resources and quality collaborative optimization are planned as a whole, and the quality control accuracy is improved. According to the method, a traditional post-test type static back-end quality management mode is converted into a front-end-middle-end-back-end full-process construction period control mode which takes quality guarantee and construction period compression as double targets and can be dynamically adjusted, so that the optimal control of the construction period is realized on the premise of ensuring that the product quality is not lower than a preset threshold value, and the product quality is ensured to be higher than the preset threshold value. The defects that in existing equipment production management, construction period-resource-quality balance cannot be dealt with, and production pressure fluctuation is difficult to adapt can be overcome, and the requirements for high efficiency and stability of equipment production are met.

The present application discloses a comprehensive quality management abnormal fluctuation monitoring and identification system and method, the system includes: a first monitoring system, used to monitor the operating conditions of the target object to be measured, and send the first abnormal operating condition to the server platform after monitoring the first abnormal operating condition; the server platform, used to obtain the first influencing factor type corresponding to the first abnormal operating condition; obtain the corresponding influencing factor characteristic data; determine the actual influencing factor type of the first abnormal operating condition based on the influencing factor characteristic data; increase the warning value corresponding to the management clause data to obtain the corresponding first warning value; when the first warning value exceeds the warning threshold, a warning prompt signal is issued. By using the solution of this application, the timeliness of the modification of the management clause content and the processing efficiency of the modification and improvement work can be improved, so as to improve the high matching degree between the management system and the actual situation and ensure the quality of enterprise / project operation.

The application discloses a kind of noble metal product quality traceability and digital management system, it is related to noble metal quality management technical field, to solve the technical problem that current traditional pre-production post-detection mode can cause noble metal resource waste, including data acquisition module, customization quality control module, real-time analysis early warning module, data traceability management module, block chain storage module, and process self-learning optimization module, each module is modular design and is configurable component, data intercommunication linkage operation is realized between modules through standard interface.The application realizes the dynamic monitoring and instant adjustment effect of production process parameters by embedding real-time analysis early warning module and customization quality control module, solves the problem that current traditional pre-production post-detection mode can cause noble metal resource waste.System uses production detection mode, real-time acquisition key quality control point data in production process, reduces noble metal loss rate, realizes resource zero waste.

This invention discloses a staged quality inspection method and system for SMT (Surface Mount Technology) semi-finished products, specifically relating to the field of electronic manufacturing quality management technology. The method includes the following steps: quality inspection is performed at each stage of the production line, the inspection results are recorded and a result set is formed, and early signs of production rhythm imbalance are identified using time interval distribution analysis; if imbalance is present, the defect frequency fluctuation index and the production line dynamic disorder index are further calculated to quantify the dynamic fluctuations and systemic problems of non-conforming phenomena; the two indices are input into a pre-trained machine learning model, and the model output distinguishes the quality status of the production line as high quality or low quality; for low-quality production lines, optimization is performed according to a preset adjustment strategy; this method can monitor the quality status of the production line in real time, accurately distinguish between accidental and non-accidental problems, improve quality management efficiency, ensure stable operation of the production line, and reduce the proportion of non-conforming products.

An underground pipeline quality management and control method belongs to the field of underground pipeline quality management and control and comprises the following steps: step 1, performing three-dimensional surveying and mapping by adopting a positioning device under a WGS84 coordinate system manufactured based on an inertial navigation principle; 2, observing the internal state of the pipeline by using an endoscope technology, and quantitatively monitoring the deformation of the pipeline by using laser ranging to realize the detection of defects in the pipeline; and 3, measuring the length of the pipeline and positioning the defects of the pipeline by using a speedometer, so that the defects in the pipeline are efficiently repaired. According to the invention, the underground position of the pipeline and the internal defects of the pipeline can be detected conveniently, so that accidents caused by unclear position or internal defects of the pipeline are avoided, and long-term stable use of a cable line is ensured.

The present application belongs to the technical field of image processing, and particularly relates to a mine support product quality management and control method and system, which comprises the following steps: generating a target image sequence; performing model matching and image mapping on the target image after edge detection to obtain a target edge; extracting a target image feature point to generate a registration target image and a registration target image sequence; positioning a target area, calculating a target main shaft direction angle; calculating a target centroid coordinate according to a target area pixel point abscissa, ordinate and total number of pixel points; calculating a target asymmetric distortion degree according to the distance between the target centroid coordinate and the target main shaft straight line and the total number of target pixel points; in the registration target image sequence, calculating an anchor rod quality risk index, drawing an anchor rod quality risk baseline, and analyzing according to a preset threshold to trigger the system to issue an alarm and prompt replacement of the anchor rod. The present application realizes dynamic management and control of the anchor rod throughout its life cycle.