19 results about "Quality standard" patented technology

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.

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 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 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.

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 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.

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.

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.

This invention discloses a testing method and system for an intelligent reading device, comprising the following steps: placing the intelligent reading device on a testing device; setting a first test rule and a second test rule for the intelligent reading device; performing a reading performance test on the intelligent reading device based on the first test rule to obtain the reading performance test result; performing a durability test on the intelligent reading device based on the second test rule to obtain the durability test result; and determining the quality test result of the intelligent reading device based on the reading performance test result and the durability test result. In this invention, the testing method is applied to the quality control stage of the intelligent reading device testing process, which helps to improve the quality reliability of the intelligent reading device, significantly enhances its quality standards and competitiveness, and has broad market application prospects.

This invention discloses a method for optimizing wafer lamination process. This method designs experiments based on the parameters involved in the wafer lamination process using the Design of Elements (DOE) matrix design method. By conducting experiments in the specified order, the process parameters that maximize the wafer lifespan are obtained as the optimized process parameters. The process parameters obtained by this method can ensure that the cutting blade can provide early warning before the end of its lifespan. The safety margin ensures that products already installed on the equipment can be safely processed and meet the process quality standards without defective products.

The invention provides a food contact material product quality standard traceability system and method. The food contact material product quality standard traceability system comprises a multi-dimensional data acquisition module which is used for acquiring raw material traceability data, production process carbon footprint data, product quality detection data, circular economy attribute data and tax associated data; the block chain evidence storage module is used for carrying out uplink evidence storage on the key data acquired by the multi-dimensional data acquisition module and generating a product digital fingerprint which cannot be tampered; the green tax intelligent association engine is used for matching green tax preferential policies of a target market based on the circular economy attribute data; a dynamic compliance early warning module, a circular economy contribution value calculation module and a traceability information service platform. The food contact material product quality standard traceability system and method provided by the invention have the advantage of being capable of realizing credible acquisition, evidence storage, analysis and application of full-life-cycle data of the product.

The invention provides a method for detecting the content of five components in melastoma dodecandrum and application of the method. Specifically, the invention provides a method for detecting the contents of chlorogenic acid, codonopsis pilosula glycoside I, luteoloside, apigenin 7-O-beta-D-glucoside and lobetyolin in the centella asiatica. The detection method disclosed by the invention is accurate, high in sensitivity, good in repeatability and reliable in result, provides a basis for quality control and evaluation of the round-clock flowers, and has a good application prospect in formulating a round-clock flower quality standard, reasonably developing and utilizing resources and the like.

The invention discloses a design document generation method and device, equipment, a medium and a product. Relates to the technical field of artificial intelligence. The method comprises the steps that based on generation constraint conditions and chapter structures of a demand document and a design document, a first draft of the design document is generated through a large language model, content enhancement is conducted on the first draft, and an enhanced design document is generated; for each preset cue word template, first background knowledge is obtained based on the associated knowledge retrieval key of the template, and review prompt information is generated according to the enhanced design document, the first background knowledge and the review rule set of the template; inputting the review prompt information into the large language model, and generating review response information of the template; generating a comprehensive review result according to the review response information; and if the enhanced design document does not meet the preset quality standard, generating an optimization instruction based on the comprehensive review result, so that the big language model optimizes the enhanced design document based on the optimization instruction. And the design document quality and the writing efficiency can be improved.

This invention relates to a method and application for identifying standard decoctions of Dryopteris crassirhizoma and its adulterants. The method includes the following steps: extracting standard decoctions of Dryopteris crassirhizoma and its adulterants using extraction solvents to prepare test solutions; dissolving a reference standard of oxaliplatin AB using a dissolving reagent to prepare a reference solution; and performing high-performance liquid chromatography (HPLC) on the test solution and the reference solution to obtain the content of oxaliplatin AB in the standard decoction of Dryopteris crassirhizoma. This invention establishes a method for determining the content of oxaliplatin AB, a characteristic component of the standard decoction of Dryopteris crassirhizoma, thereby enabling qualitative and quantitative identification of the standard decoction, ensuring its safe use, and for quality control of the standard decoction. The establishment of this method not only provides a basis for establishing quality standards for the standard decoction of Dryopteris crassirhizoma, but also provides an important reference for establishing quality standards for Dryopteris crassirhizoma granules and related traditional Chinese medicine preparations.

The invention discloses a preparation method and a quality detection method of a ligusticum wallichii standard decoction, and relates to the technical field of quality research of traditional Chinese medicinal materials. The method comprises the following steps: weighing a proper amount of ligusticum wallichii decoction pieces, putting the decoction pieces into a marmite, decocting twice, adding 9 times of water for soaking for 30 minutes for the first time, boiling with strong fire, and then decocting with slow fire for 30 minutes; 7 times of water is added for the second time, the mixture is boiled with strong fire and then decocted with slow fire for 20 min, the liquid medicine is filtered with 200 meshes, the filtrate is cooled to the room temperature in a cold water bath, the two filtrates are combined, vacuum concentration is conducted at the temperature of 50 DEG C, vacuum concentration is conducted at the absolute vacuum degree of 30-40 mbar until the weight ratio of the medicinal materials to the fluid extract is about 1: 1, concentrated liquid is collected, and freeze drying is conducted to obtain a sample. According to the method, key quality indexes such as the main content, the characteristic chromatogram and the extract of the ligusticum wallichii after the decoction is prepared are measured, the transfer rate is investigated, the component transfer condition from decoction pieces to the decoction is measured through objective quality standards, and the quality degree and effectiveness of the decoction are ensured.

The application provides a process parameter optimization method and device based on an industrial internet, equipment and a medium, relates to the fields of big data and industrial internet. The method comprises the following steps: receiving a process parameter optimization instruction, obtaining original process parameters of a target product and quality detection data corresponding to the target product, analyzing and processing the quality detection data, determining a quality detection analysis result of the target product, inputting the original process parameters into a pre-constructed process parameter optimization model when the quality detection analysis result indicates that the quality of the target product does not meet a preset quality standard, and obtaining target process parameters by optimizing the original process parameters; wherein the quality of a product manufactured based on the target process parameters meets the preset quality standard. The method improves the accuracy, timeliness and automation level of process adjustment, effectively guarantees the stability of quality and intelligent control of the production process.

This invention relates to the field of laser holographic image generation technology, and more particularly to a method and apparatus for generating thin-film holograms. The system includes steps S1: thin-film pretreatment; S2: coating operation and continuity detection; S3: quality ratio analysis of the coated thin film; S4: holographic image inspection; and S5: adjustment of coating quality inspection parameters. This invention performs surface pretreatment on the thin film, conducts a coating operation and performs continuity detection on the coating liquid, performs quality ratio analysis when the detection result indicates local discontinuity, and implements corresponding recoating measures. After illumination treatment, image recognition technology is used to inspect the quality of the hologram on the thin film, and relevant parameters are adjusted based on quality fluctuations during the coating process to ensure that the final product meets quality standards. This invention features efficient and stable coating technology, ensuring thin-film quality while improving production efficiency, and has broad applicability to the production of anti-counterfeiting labels, trademarks, and custom stickers.