70 results about "Quality management system" patented technology

The invention relates to a fabric flaw detection and traceability system based on edge calculation and computing power scheduling, which is suitable for intelligent quality control in a textile production process. The system comprises an acquisition unit, a modeling unit and the like. The acquisition unit acquires fabric images and environmental data through a multispectral imaging device and a process parameter sensor, and constructs time-aligned multi-modal feature tensors. The modeling unit extracts texture features by using unsupervised comparative learning in combination with fabric material characteristics, and generates potential texture fingerprint vectors. And the detection unit adopts a target detection network of a channel attention mechanism to identify fabric flaws and output positions, types and severity. The traceability unit analyzes correlation between defects and process parameters through time sequence causal reasoning, and constructs a causal atlas. And the optimization unit generates a process optimization vector according to the causal atlas and the risk score, and realizes visual display and edge control feedback, thereby constructing a real-time defect control and explainable traceability-oriented closed-loop quality management system.

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

This invention relates to a fabric defect detection and traceability system based on edge computing and computing power scheduling, applicable to intelligent quality control in textile production processes. The system includes a data acquisition unit and a modeling unit. The data acquisition unit acquires fabric images and environmental data through multispectral imaging equipment and process parameter sensors, and constructs a time-aligned multimodal feature tensor. The modeling unit combines fabric material characteristics and uses unsupervised contrastive learning to extract texture features and generate potential texture fingerprint vectors. The detection unit uses a target detection network with a channel attention mechanism to identify fabric defects and outputs their location, type, and severity. The traceability unit analyzes the correlation between defects and process parameters through temporal causal reasoning, constructing a causal graph. The optimization unit generates process optimization vectors based on the causal graph and risk score, and realizes visualization and edge control feedback, thereby constructing a closed-loop quality management system for real-time defect control and interpretable traceability.

The invention discloses an automobile safety part welding quality management system, and relates to the field of quality detection. Comprising a data acquisition layer for acquiring multi-dimensional data of a weldment by using weldment quality detection equipment; the data processing layer is used for processing the collected data, a defect evaluation model is arranged in the data processing layer, processed output is input into the defect evaluation model, and a weldment quality evaluation result is output; and the defect classification module is used for classifying the weldments with defects according to the output quality evaluation result. By establishing the standardized welding data management system, on one hand, welding quality evaluation can be carried out after welding multi-dimensional data are collected and fused, the welding quality evaluation precision is improved, on the other hand, welding defective weldments are classified, analysis and welding process optimization are facilitated, and the welding quality is improved. And meanwhile, distributed storage is adopted for data storage, and dynamic space optimization can be performed on each storage unit, so that data over-limit loss is prevented, and the data read-write operation fluency of the system is also improved.

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

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

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

The invention discloses a positioning and anchoring device and method for a foam core mold and a reinforcement cage of a hollow slab girder, the device comprises a connecting part connected with the foam core mold, an anchoring part for anchoring the reinforcement cage, a positioning part positioned on a pedestal and a bolt connecting pair, and quick installation and reutilization are realized through a threaded connection and bolt fixing technology. According to the method, a real-time monitoring system is introduced, a correction instruction is generated in combination with data collection and a closed-loop control algorithm, constructors are assisted in accurately adjusting the position of the reinforcement cage, and dynamic errors in the pouring and vibrating process are effectively restrained. And meanwhile, a data-driven quality management system is constructed, and digital recording and process optimization of the construction process are realized. According to the invention, multiple construction scenes are compatible through modular design, the positioning precision and the construction efficiency are remarkably improved, the material waste is reduced, and a reliable guarantee is provided for the structural safety and durability of the prefabricated hollow slab beam.

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

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

The present invention discloses a three-dimensional design and quality management system for wind power ring forgings based on 5G communication, which belongs to the field of wind power equipment manufacturing technology. The system includes: a modeling module for constructing a parametric three-dimensional design model and outputting design parameters for quality assessment and defect identification; a process data acquisition module for real-time acquisition of process data such as temperature, pressure, and vibration in key structural areas; a defect identification module for fusing image and signal data, and outputting defect type, location, and its sensitivity impact; a quality assessment module for quantitatively scoring product quality based on a scoring function and disturbance response parameters; a feedback control module for identifying dominant deviations and generating control instructions when the scoring is abnormal; and a 5G communication module for realizing high-speed data interaction between modules. The present invention realizes closed-loop control of design, manufacturing, testing, and evaluation, improves the manufacturing quality and efficiency of ring forgings, and is suitable for the manufacturing scenarios of large-scale, high-reliability wind power structural parts.

The application discloses a large-size photovoltaic cell doping / oxidation / annealing process adaptive quality management system, which comprises a data acquisition layer, an intelligent decision-making layer and a control execution layer; the data acquisition layer collects process parameters through doping, oxidation and annealing PLC systems, constructs a time-space aligned process data cube, and outputs a multi-dimensional feature matrix containing time x process x parameter; the intelligent decision-making layer analyzes the multi-dimensional feature matrix by using a random forest hidden crack classification model and outputs a hidden crack risk grade; the control execution layer comprises a dynamic compensation strategy composed of a diffusion furnace temperature control module and an annealing cooling compensator, is used for generating an OPC UA instruction according to the hidden crack risk grade, and triggers an annealing furnace PID regulator through the OPC UA instruction to dynamically adjust process parameters of the annealing furnace; the application solves the data island problem by integrating multi-process PLC data and the random forest model, realizes high-precision hidden crack prediction, and significantly improves the quality detection efficiency.

The application relates to the technical field of quality management systems, and particularly discloses a textile dyeing production quality management system based on multi-source data monitoring, which comprises the following modules: a critical recognition module that constructs a continuous airflow field model and identifies a vortex core area in combination with dynamic modal decomposition; a migration analysis module that maps the vortex core area to a dye concentration gradient field and identifies a vortex dominant linkage; a migration analysis module that couples and constructs an airflow-dye coupling transfer function, quantifies migration intensity and obtains a migration intensity index; an inter-cluster extraction module that extracts color difference surge clusters based on the migration intensity index and quantifies features; and a convergence control module that judges and controls effects through a convergence regression model, so as to realize dynamic convergence regulation. The present application integrates multi-source data and physical models, realizes intelligent monitoring of the whole process from migration risk early warning, driving mechanism identification to active control, and improves the uniformity of textile dyeing and the stability of production.

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

The invention discloses a large-size photovoltaic cell doping / oxidation / annealing process adaptive quality management system. The system comprises a data acquisition layer, an intelligent decision-making layer and a control execution layer. The data acquisition layer acquires process parameters through a doping, oxidation and annealing PLC (Programmable Logic Controller) system, constructs a space-time aligned process data cube, and outputs a multi-dimensional feature matrix containing time * process * parameters; the intelligent decision-making layer analyzes the multi-dimensional feature matrix by using a random forest subfissure classification model, and outputs a subfissure risk level; the control execution layer comprises a dynamic compensation strategy composed of a diffusion furnace temperature control module and an annealing cooling compensator, and is used for generating an OPC UA instruction according to the subfissure risk level, triggering an annealing furnace PID regulator through the OPC UA instruction, and dynamically regulating process parameters of the annealing furnace; according to the method, the multi-process PLC data and the random forest model are integrated, the problem of data islands is solved, high-precision subfissure prediction is achieved, and the quality detection efficiency is remarkably improved.

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

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

The invention discloses a semen sample quality management system based on federated learning and dynamic time sequence prediction, which is characterized in that a data acquisition module (100) is used for cleaning received original semen sample detection data, a federated learning cooperation module (200) adopts an improved Paillier homomorphic encryption algorithm to carry out encryption transmission on local model gradient parameters, and a dynamic time sequence prediction module (200) is used for carrying out dynamic time sequence prediction on the local model gradient parameters; the dynamic time sequence prediction module (300) is used for extracting quality characteristics with a time sequence dependency relationship from detection data of a semen sample and carrying out online incremental training on a prediction model; the multi-modal data fusion module (400) is used for extracting a genome feature sequence of a semen sample and analyzing environmental parameters stored in the sample; and the quality evaluation decision module (500) fuses the time sequence prediction model and the genome feature sequence. According to the method, multi-center data collaborative modeling is achieved through a federated learning architecture, the online incremental learning ability is achieved in combination with the multi-modal data fusion technology, the prediction model can be continuously optimized, and the method effectively adapts to the change of sample features.

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

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

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

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

The invention provides an equipment design quality management system and method and electronic equipment, and relates to the technical field of quality management, and the system comprises an information obtaining module which is used for obtaining project information; the potential risk list generation module is used for matching historical problems and generating a risk list; the distribution module is used for sending the potential risk information in the potential risk list to a designer corresponding to the potential risk information according to the project information; the quality detection module detects quality data according to a period, and judges whether the design project has an occurred design quality problem or not; the information feedback module is used for disassembling part numbers, names, descriptions, types and solutions from the problem data; and the quality index calculation module is used for generating a quality level evaluation report of the project in the preset period. According to the invention, the quality management efficiency is improved, and the quality management level is also improved.

The invention discloses an electromechanical pipeline installation quality management system based on data analysis, and relates to the related technical field of installation quality management, and the system comprises a scene construction module which is used for constructing a target scene and configuring an electromechanical pipeline component distribution database; the initialization module is used for initializing an installation task set of the electromechanical pipeline; the acquisition monitoring module is used for configuring sampling nodes based on the installation task set and executing installation data acquisition; the quality scoring module is used for synchronizing the installation data set and the target scene to a quality scoring model, executing electromechanical pipeline installation quality scoring and establishing a quality scoring result; and the packaging management module is used for carrying out associated storage management on the quality scoring result and the installation task set. The technical problems that in the prior art, electromechanical pipeline installation quality management efficiency is low, and real-time monitoring and dynamic evaluation are difficult are solved, and the technical effects that real-time monitoring and dynamic scoring are achieved, the automation level of installation quality management is improved, and data traceability is enhanced are achieved.

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

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

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

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

The invention provides a coke rating method and rating system based on a multi-scale residual neural network. The method comprises the following steps: S1, establishing terminal equipment and a coke quality management system; s2, acquiring coke audio information, and performing audio feature extraction and analysis; s3, forming a function by using the coke components, and marking a quality label on the coke sample in combination with experience; s4, constructing a coke quality rating model; s5, obtaining a quality evaluation result of the current coke sample, and generating a corresponding quality grade; and S6, displaying the quality grade of the coke sample on a terminal equipment interface, and completing the final quality grade of the coke quality. The invention provides a set of complete system from terminal information collection to result display, can unify and standardize the evaluation of the coke quality grade, is beneficial to timely and accurate judgment of the quality level of the coke, promotes judgment and management of the coke, improves the efficiency of coke quality rating management, and enables the coke rating process to be more scientific and normative.