56 results about "Quality standard" patented technology

The invention discloses a product traceability direction management and control system based on full-process monitoring, and relates to the technical field of product traceability management. The full-process management and control platform is in communication connection with a product data acquisition module, a product identification analysis module, a product data management module, a data traceability analysis module, a product abnormity management module, a process optimization module and an interaction management module. According to the product traceability direction management and control system based on full-process monitoring, through comprehensive monitoring and recording of raw material sources, production dates, processing details and quality inspection results, it is ensured that products meet preset quality standards in each production link, once any deviation is found, the system can immediately give out early warning, and the product traceability direction management and control system is convenient to use. In addition, a large amount of data is analyzed through a machine learning algorithm, key factors influencing the product quality can be recognized, and therefore a scientific basis is provided for quality improvement.

The invention relates to a quality standard retrieval tool and method based on a large language model. The method comprises the following steps: storing a quality standard file, embedded vector data corresponding to the quality standard file and a mapping relation between the quality standard file and the embedded vector data into a quality standard file knowledge base; question vector data converted from a question described by a natural language is received, embedded vector data most similar to the question vector data is retrieved from a quality standard file knowledge base, and a quality standard file text corresponding to the embedded vector data is a related support document; recording the historical retrieval question and the corresponding retrieval result as historical question and answer information, and summarizing a preset response rule, the current retrieval question, the related support document and the historical question and answer information into cue words; and adopting a pre-trained large language model to generate a retrieval result according to the cue word.

The invention provides a process parameter optimization method and device based on an industrial internet, equipment and a medium, and relates to the field of big data and the field of the industrial internet. The method comprises the steps of receiving a process parameter optimization instruction, obtaining original process parameters of a target product and quality detection data corresponding to the target product, performing analysis processing on the quality detection data, determining a quality detection analysis result of the target product, and outputting the quality detection analysis result. When the quality detection analysis result shows that the quality of the target product does not meet the preset quality standard, inputting the original process parameters into a pre-constructed process parameter optimization model to optimize the original process parameters to obtain target process parameters; wherein the quality of the product manufactured based on the target process parameters meets a preset quality standard; according to the method, the accuracy, the timeliness and the automation level of process adjustment are improved, and the quality stability and the intelligent control of the production process are effectively guaranteed.

The invention particularly relates to a code writing, checking and modifying method based on a large model. According to the code writing, checking and modifying method based on the large model, a fine-tuning large language model is adopted to analyze user requirements, and multi-language initial codes are generated; executing deep code review through a static analysis engine, wherein the deep code review comprises syntax tree verification, security vulnerability mode matching and API dependency chain detection; executing the automatically generated test case set in an isolation environment, monitoring operation indexes in real time, and generating a defect thermodynamic diagram; and driving the large model to perform iterative code reconstruction based on a defect analysis result until it is confirmed that a preset quality standard is met. The code writing, checking and modifying method based on the large model is suitable for multiple languages, the defect rate of codes is reduced, the software development period is prolonged, the labor cost is reduced, and the vulnerability detection rate is greatly increased.

The invention discloses a material purchasing management system. The system comprises a supplier management and evaluation module; the system is responsible for collecting and analyzing supplier basic information, historical performance, quality evaluation, after-sales service data structured data, social media data and industry news unstructured data in real time, and dynamically evaluating suppliers. The supplier management and evaluation module transmits an evaluation result to the purchase order and quality standard docking module and the product quality verification and detection module; and the product quality verification and detection module is responsible for carrying out intelligent quality verification and detection on samples or preliminary batches provided by the recommended suppliers before purchase decision making by adopting the Internet of Things technology and automatic detection equipment. The product quality verification and detection module carries out quality verification and detection on samples or preliminary batches provided by recommended suppliers before purchase decision making, it is ensured that products meet the set quality standard, and subsequent problems caused by substandard product quality are effectively avoided.

The invention provides a mapping analysis method, system, equipment and medium for chip carrier production data and quality standard data, and belongs to the technical field of chip carrier production, and the method comprises the following steps: cleaning historical production data to obtain a standard data set, screening out a key process parameter set, and grouping the data according to production processes. Extracting statistical features of the key parameters to form a process feature set, and performing mapping matching on the process feature set and a preset standard quality feature set to generate a mapping relation set; and analyzing the mapping relation set based on the consistency evaluation model, outputting an evaluation result, and generating a quality analysis report. And through key parameter set screening and process feature extraction, the analysis accuracy is improved. The mapping and quantitative comparison of the production data and the quality standard in the multi-process dimension are realized, and the deviation process can be positioned. Based on automatic analysis of the consistency evaluation model, abnormal processes can be identified, potential process reasons can be traced, and the product yield and the production stability are effectively improved.

The invention provides a quality rating and repairing method for a buried steel skeleton reinforced polyethylene composite pipe. The quality rating and repairing method comprises rating standard formulation, a measuring method, a rating process, repairing and replacing suggestions and the like. Through visual observation and accurate measurement, quality standards of different grades are clearly divided, and corresponding repair or replacement suggestions are given. According to the method, multiple detection means are combined, the accuracy and reliability of the rating result are ensured, and a scientific basis and technical support are provided for safe operation and effective management of the pipeline. The method is suitable for evaluating the quality condition of the buried pipeline after excavation and guiding subsequent maintenance and repair work.

A quality review management system may be used to analyze the operation of manufacturing processes within a plant based on data collected by various data sources in the plant, such as batch executive applications, to automatically detect, store, and display exceptions within those processes for use by a quality review engineer to determine if the process operation meets certain quality standards. The quality review management system includes a configuration application that enables a user to create one or more exception rules, an exception engine that uses plug-ins in various devices to collect process data and to analyze the process data using the rules to detect one or more exceptions within the process, and a review application that enables quality review personnel to review each determined exception for resolution purposes.

The present invention discloses a flange processing control system based on the Internet of Things. The present invention relates to the field of flange processing control technology and solves the technical problem that data acquisition and analysis means are limited in the processing process, there is a lack of a systematic analysis and matching mechanism, and the product quality does not meet the requirements. The present invention can scientifically determine the flange material according to the processing requirements through the collaborative work of the processing information acquisition module and the preliminary processing analysis module, and use appropriate cutting technology and equipment for processing. By utilizing the Internet of Things technology, key data such as flatness and roughness can be obtained in real time during the processing process. Through precise measurement means and comparative analysis mechanisms, it is ensured that the processed flange products meet strict quality standards and improve product quality stability. The processing plan selection module uses advanced means such as time series analysis to conduct in-depth analysis of equipment operation data, and can quickly find similar processing records that meet current processing requirements and generate accurate control information.

The present application relates to the technical field of banknote production, and provides an integrated production system and method for banknote cutting, inspection, and sealing, a device, a medium, and a chip. The production system comprises: an automatic banknote feeding module, which uses a first numerical value to divide a large sheet product to form large sheet stacks, and performs, by means of vibration, banknote alignment and counting on the large sheet stacks; a cutting module, which cuts the large sheet stacks to form small sheet products, and uses a second numerical value to divide the small sheet products into small sheet stacks; an inspection module, which performs quality inspection on the small sheet stacks, so as to determine whether the small sheet stacks meet quality standards; a defective banknote processing module, wherein if the small sheet stacks do not meet the quality standards, the small sheet stacks enter the defective banknote processing module; a counting and transfer module, wherein if the small sheet stacks meet the quality standards, the small sheet stacks enter the counting and transfer module, and said module counts the small sheet stacks; a plastic sealing module, which performs thermoplastic sealing on the small sheet stacks; and a boxing module, which is used for putting the plurality of small sheet stacks into a storage box.

The present application provides a parameter quality management method and related apparatus and medium program product, which can be applied to a server and includes: obtaining a first parameter scorecard used to characterize the quality status of a target parameter; updating a first upper specification limit USL and / or a first lower specification limit LSL of component parameters and process equipment parameters in the target parameter to obtain a second upper specification limit USL and / or a second lower specification limit LSL; updating the first parameter scorecard based on the second upper specification limit USL and / or the second lower specification limit LSL to obtain a second parameter scorecard; and determining the updated parameter quality standard of the target parameter based on the second parameter scorecard. In this way, the parameter quality standard can be updated in real time, improving user production efficiency.

The invention provides a method and system for automatically generating a high-quality large-scale data set, and the method comprises the steps: constructing a knowledge graph according to an original corpus of a specific field; based on the knowledge graph, constructing a vertical question-answering system through at least two paths; generating question-answer pairs through a vertical question-answer system; optimizing and evaluating the question and answer pair according to a quality standard to obtain an evaluation result; and integrating qualified evaluation results into a final data set. According to the method, the knowledge graph is taken as a basis, a data set of a professional field is generated through a self-asking and self-answering mechanism, a large number of question and answer pairs are generated in batches in a high-automation manner, a data set with high generalization and high quality is generated, the data set generation efficiency and scale are effectively improved, and the method can be used for model training. According to the question and answer pairs, a top-down method is adopted, through community division and community reports, basic question and answer based on triads can be achieved, and global and inductive question and answer pairs can be generated.

The present application relates to the technical field of package detection, and particularly relates to a fan-out package detection method and system based on photoetching positive glue, which comprises the following steps: dividing a photoetching positive glue developing area into units to obtain a plurality of developing units; performing three-dimensional profile scanning on a copper pillar array after etching of each developing unit to obtain size characteristic parameters of the copper pillar array; collecting a circuit plating image of each developing unit and performing microscopic feature identification thereon to obtain microscopic characteristic parameters; comparing and analyzing the size characteristic parameters and the microscopic characteristic parameters with corresponding preset quality standards respectively for each developing unit, and generating an out-of-standard feature set when any one of the size characteristic parameters and the microscopic characteristic parameters exceeds the preset quality standards; performing quality evaluation on the out-of-standard feature set to obtain a quality score corresponding to each developing unit; and realizing accurate positioning of local defects of the developing area to avoid misjudgment or missed detection.

The present invention relates to the field of thickness detection technology, comprising: a detection table, on which a detection box is installed, and a detection hole is opened inside the detection box; a conveying part, the conveying part is used to drive the thermal insulation cotton to pass through the middle of the detection hole; a detection part, the detection part comprises a detection block fixed at the top of the detection hole and a detection frame installed at the bottom of the detection block, the top of the detection frame is opened with a detection groove, and the detection groove is sleeved on the bottom of the detection block; when the thermal insulation cotton of the present invention passes through the bottom of the front marking wheel, the detection frame is lifted up, and the detection groove moves above the detection block. At this time, the distance sensor is used to detect the change in the distance between the bottom of the detection block and the bottom of the detection groove, and the height of the thermal insulation cotton is calculated. In this way, the thickness of the thermal insulation cotton can be measured in real time and accurately when it passes continuously, ensuring that each part of the thermal insulation cotton meets the preset quality standards, thereby greatly improving production efficiency and product quality control.

The invention relates to a computer-implemented method and technical system for ensuring a quality standard for a code sequence (CS) generated with the aid of a generative AI model (LLM) to fulfill one or more features of a software application to be developed in a software development project, wherein the quality standard is defined by a minimum degree of fulfillment of this or these features, optionally according to their classification in the software development project. The method comprises the following steps, which can be executed in particular with the aid of at least one processor of the technical system (S): a) Extracting this / these feature(s) from artifacts of the software development project, classifying them if necessary, and relating them to each other if there are several features, whereby the quality standard is defined by a minimum degree of fulfillment of this or these features, possibly according to their relation to each other and possibly according to their classification in the software development project; b) Providing one or more rejected code sequence examples in a memory (REP) derived from the information obtained in step a) that fall below the specified minimum level of fulfillment and / or that result from previously rejected code sequences generated by the generative AI model; c) Enriching at least one captured prompt (P), which initiates the generation of the code sequence by the generative AI model, with context formed from the one or more extracted features and with the one or more sorting examples, and applying the at least one enriched prompt to the generative AI model; d) Capturing the code sequence generated using the enhanced prompt and evaluating the generated code sequence based on the quality scale; and e) Outputting the generated code sequence if the result of the evaluation from step d) is positive, by meeting or exceeding the specified minimum level of fulfillment.

The application relates to the technical field of silicon crystal bar measurement and classification, and discloses a silicon crystal bar diameter measurement and intelligent classification method based on point cloud segmentation fitting, which comprises the following steps: obtaining the original three-dimensional point cloud of a silicon crystal bar to be measured, carrying out pretreatment, extracting a main shaft and normalizing coordinates to obtain aligned three-dimensional point cloud; segmenting and cutting the aligned three-dimensional point cloud along the main shaft direction, screening a plurality of effective subsegments, and carrying out local cylindrical fitting on the effective subsegments to obtain local geometric parameters; carrying out feature statistical analysis according to the local geometric parameters and carrying out deviation compensation; matching the compensated geometric feature parameters with preconfigured product model templates, identifying and determining the model to which the silicon crystal bar to be measured belongs, and carrying out quality judgment and outputting results according to the quality standard of the model.

A quality inspection system can be used to analyze the operation of a manufacturing process within a plant based on data collected by various data sources (e.g., batch executor applications) in the plant to automatically detect, store, and display anomalies in these processes for use by quality inspection engineers to determine whether the process operation meets certain quality standards. The quality inspection system includes: a configuration application that enables a user to create one or more exception rules; an exception engine that uses rules to analyze process data to detect one or more anomalies in the process; and an inspection application that enables quality inspectors to inspect each determined anomaly for resolution. In addition, the quality review system collects metadata about the process plant for use in detecting anomalies or after detecting anomalies, and stores the metadata with the anomaly records for use by inspectors. Therefore, the system provides inspectors with contextual information about the detected anomalies, which in turn enables inspectors to better understand and handle the anomalies.

A system and method for continuous batch monitoring of key quality characteristics of the production of precisely targeted FAC, optimally HOCl, through use of pressure, temperature, pH, ORP, tonicity sensors and spectroscopy instruments measuring the dynamic averages of product in a circulating vessel that informs the input production system through a dynamic feedback loop to make corrective formulations of key characteristics such that corrections occur to the constantly monitored HOCl solution in order to meet verified quality standard at the storage vessel's point of dispensing.

The application relates to the technical field of casting, and discloses an intelligent casting process whole-flow optimization system and method, which comprises the following steps: digitizing and analyzing casting drawings and process flow documents to generate a structured process table; based on the structured process table, using a DeepSeek-NLP model to perform multi-round question answering, outputting process structure analysis results and initial process parameter suggestions; based on the process structure analysis results and the initial process parameter suggestions, constructing a three-dimensional process model, simulating a casting process based on a simulation tool, and generating simulation results; testing the simulation results; if there are defects that do not meet quality standards or process parameters that do not match, feeding back correction requirements to an AI intelligent analysis module, triggering iterative optimization of process parameters, and completing closed-loop optimization of the process flow. The application can significantly shorten the parameter optimization cycle, improve the intelligent level of production and the product yield.

This invention discloses a method for synergistic optimization of process parameters and ion content in penetrant production, belonging to the field of chemical material production technology. This invention constructs a full-process monitoring and quantitative evaluation mechanism to dynamically control the entire process of synergistic optimization of process parameters and ion content in penetrant production. This includes data acquisition, model building, parameter optimization, and feedback adjustment. By collecting core process parameters and system ion content data throughout the entire penetrant production process, multi-objective synergistic optimization is performed. Multiple constraints are set to ensure the feasibility of optimization, achieving precise matching of process parameters and ion content. Under the premise of meeting strict quality standards and environmental protection requirements, the dual goals of improving production efficiency and reducing costs are achieved. A sensor array monitors product performance in real time, and based on a correlation model, key deviation parameters are accurately located and dynamically adjusted in multiple steps, rapidly responding to production fluctuations and avoiding production instability caused by parameter mutations, effectively controlling product performance deviations.

The invention relates to the technical field of project management, and discloses a real-time process rationality evaluation method and system for project management, and the method comprises the steps: classifying and storing parameters such as predicted duration, resource consumption standard, quality standard and the like of a process, obtaining actual duration, actual resource consumption and actual quality result dynamic data, and carrying out the real-time process rationality evaluation. And then constructing a mathematical model of the duration deviation index, the resource deviation index and the quality deviation index, if any evaluation index does not conform to the corresponding standard interval, indicating that the project process is unreasonable, aiming at improving the content of the non-conforming corresponding standard interval, if any evaluation index does not conform to the corresponding standard interval, calculating a comprehensive rationality index, and determining that the project process is unreasonable. The system continuously collects data, updates indexes, triggers an early warning mechanism, adjusts parameters of substandard procedures until all indexes reach the standard, simultaneously covers time, resources and quality, avoids one-sidedness of single-dimension evaluation, and reduces errors of manual summarization and subjective judgment.

The present application relates to the technical field of tunnel kiln, and discloses a tunnel kiln equipment for directly producing ceramic zinc oxide, which comprises: a kiln body provided with multiple functional areas, each of which is provided with a temperature control unit, and each temperature control unit comprises multiple temperature control sub-units; a setting module, which acquires quality standards in the production process of ceramic zinc oxide, generates production requirement information of each type of data in each functional area according to the quality standards; and a control module, which controls the temperature of the temperature control sub-units according to the production requirement information. The present application finely maps the temperature curve by considering multiple factors, so that the temperature control is more accurate and stable.

The invention provides a dynamic detection method and device combined with sub-runner product quality analysis, and relates to the technical field of automatic detection.The method comprises the steps that K positioning serial number identifiers are generated; obtaining K sub-runner product quality inspection information sets, and performing same-index deviation identification on the K sub-runner product quality inspection information sets and the product quality standard information to generate K sub-runner product quality inspection deviation sets; obtaining K first detection coefficients; k sub-runner width intervals are obtained; building a runner extraction wheel disc based on the K first detection coefficients, and determining a first automatic detection scheme according to an extraction result; and the first automatic detection scheme is input into an automatic detection unit of the target injection molding production line for automatic product detection. According to the invention, the technical problems of low production efficiency and resource waste caused by unbalanced quality monitoring of the sub-runner in the prior art can be solved, and the technical effects of improving the production efficiency and reducing the resource waste are achieved.

The invention discloses a project cost data management method and management system, and relates to the technical field of project management, and the method comprises the steps: a data construction module obtains project cost data, and carries out the preprocessing of the project cost data to form a basic data set; performing material identification based on the basic data set, and dividing material quality grades in combination with a quality standard to form material basic data; according to the invention, through the cost accounting and price limit control module, the material cost ratio, the material quality grade Grd and the budget constraint are comprehensively analyzed, the candidate cost schemes are comprehensively evaluated, and on the premise that the total cost of the project does not exceed the budget, the scheme with the optimal quality performance is selected as the cost recommendation result; a quantitative balance relation can be established between cost control and project quality, the risk that low-price and low-quality materials enter a project is reduced, and the overall quality level of the project is improved.

The invention relates to the technical field of data processing, in particular to a self-adaptive big data processing method and system, and the method comprises the following steps: based on a big data platform, extracting sales data of tea leaves, combining quality standards of the tea leaves, analyzing the correlation between each quality standard and the sales data, and distributing a corresponding weight for each quality standard, and generating quality standard weight distribution information. According to the method, by extracting the tea sales data and analyzing the correlation between the tea sales data and the quality standards, the quality standards with low correlation are eliminated, so that the residual standards can reflect the tea quality more accurately, the data processing amount is reduced, the tea quality evaluation can be closer to reality, and the analysis of the tea quality evaluation and the storage environment change is combined, so that the tea quality evaluation accuracy is improved. The influence of the storage time period on the quality of the tea is predicted, scientific prediction is provided for keeping the quality of the tea in storage, and the tea is stored and sold under the optimal quality by adjusting storage environment parameters and optimizing storage conditions, so that the quality control and prediction of the tea are more efficient.

This invention provides a method for determining green cut quality standards that can reduce variations in the judgment regarding the finished state of the green cut surface. [Solution] The method for determining the green cut standard comprises: a specimen preparation step of preparing multiple specimens that simulate concrete used at construction sites, wherein the finished state of the green cut surface of the specimens, which is the joint surface where the green cut has been performed, differs from one another; an image data acquisition step of acquiring image data of the multiple specimen green cut surfaces; and a quality standard determination step of determining an identification specimen green cut surface for identifying green cut surfaces that meet the quality standard and those that do not from among the multiple specimen green cut surfaces captured in the image data.

The invention discloses a flange machining control system based on the Internet of Things, relates to the technical field of flange machining control, and solves the technical problems that in the machining process, data acquisition and analysis means are limited, a systematic analysis matching mechanism is lacked, and consequently the product quality does not meet the requirement. Through cooperative work of the machining information acquisition module and the preliminary machining analysis module, a flange material can be scientifically determined according to machining requirements, proper cutting technology and equipment are used for processing, and key data such as flatness and roughness are acquired in real time in the machining process by utilizing the Internet of Things technology; through an accurate measurement means and a comparative analysis mechanism, it is ensured that a machined flange product meets the strict quality standard, the product quality stability is improved, a machining scheme selection module conducts deep analysis on equipment operation data by means of a time sequence analysis method and other advanced means, similar machining records conforming to the current machining requirement can be quickly found, and the machining efficiency is improved. And accurate control information is generated.

The method comprises the following steps: initializing process parameters and setting iteration and termination conditions, presetting quality standards and constructing a target function, obtaining a current optimal process parameter evaluation index, randomly searching for new process parameters, calculating a new process parameter evaluation index, judging whether to accept or reject the new process parameters as a new current optimal solution according to an acceptance criterion, and outputting a global optimal process parameter as an optimal solution combination of the gravure printing process parameters until the termination condition is met, so as to control the printing machine to realize automatic adjustment. The gravure printing process parameter automatic optimization adjustment method has the characteristics of high efficiency, automation and cost saving.

In various embodiments, a method for quality management of a printing process of a 3D object (402) comprising a plurality of layers (404, 406) is provided. The method includes a maglev printing bed (408) onto which a printing material is deposited to manufacture a 3D object, the method including determining a weight of the printing material that has been deposited to the printing bed until now as a function of a force acting on the maglev printing bed, and comparing the calculated weight with the measured weight in a continuous manner or at discrete time intervals. The method may be used to determine, based on the comparison, whether at least one portion of the layer of the printed 3D object meets an expected quality criterion.

The invention discloses a quality control method of traditional Chinese medicine composition freeze-dried powder, which adopts an evaluation mode of combining reference index component content, fingerprint spectrum, paste yield and thin-layer chromatography to carry out quantity transfer analysis on the material reference of a Dabaixiang decoction. According to the method, comprehensive quality detection is carried out on the material reference of the Dazeheng lung-purging decoction through multiple technologies and multiple ways, and the quality standard of the material reference of the Dazeheng lung-purging decoction is drawn up, so that a scientific basis is provided for preparation development of the Dazeheng lung-purging decoction, and a thought is provided for development and research of similar prescriptions.