A cold-rolled galvanized production line comprehensive scoring system and method

Abstract

The present application relates to a kind of cold-rolled galvanized production line comprehensive scoring system and method, belong to steel metallurgy and automation control technical field, according to nine regions such as entrance section, cleaning section, furnace area, zinc pot area, cooling tower, finishing machine, passivation, oiling, packaging respectively set corresponding scoring item and scoring standard;Real-time acquisition process parameters and equipment parameters are collected by data acquisition module, and the parameters that cannot be automatically collected are manually inputted;Score is calculated by comparing each item with scoring standard;The score of each region is summarized and the comprehensive score of production line is formed, when the score is lower than the set threshold, automatically trigger root cause diagnosis and analysis, output possible reason order and suggested measures;Scoring report including comprehensive score curve, diagnosis result and early warning information can be automatically generated and pushed.

Description

Technical Field

[0001] This invention belongs to the field of iron and steel metallurgy and automation control technology, and relates to a comprehensive scoring system and method for cold-rolled galvanized production lines. Background Technology

[0002] Cold-rolled galvanizing production lines are one of the important deep-processing steps in the steel industry, and their galvanized products are widely used in automobile manufacturing, home appliances, construction and other fields. A cold-rolled galvanizing production line includes continuous process steps such as the inlet section, cleaning section, furnace area, zinc pot area, cooling tower, finishing machine, passivation, oiling, and packaging. Each step involves a large number of process parameters (such as temperature, concentration, pressure, flow rate, etc.) and equipment status parameters (such as brush roller current, nozzle status, roller surface roughness, etc.). These parameters are highly dimensional, strongly correlated, and require high real-time performance.

[0003] With the intensification of competition in the steel industry and the continuous improvement of market requirements for the quality of galvanized products, how to scientifically, comprehensively, and quantitatively evaluate the overall operational level of cold-rolled galvanizing production lines has become a core issue of widespread concern in the industry. Currently, extensive research has been conducted both domestically and internationally on process monitoring and quality management of cold-rolled galvanizing production lines, mainly focusing on upper and lower limit alarms for individual process parameters, single-point equipment status monitoring, and quality statistics for local areas. However, in terms of quantitative evaluation of overall operational levels, the following prominent technical problems still exist: First, there is a lack of scientific quantitative evaluation methods to compare the overall performance of various cold-rolled galvanizing production lines. Existing technologies typically only set upper and lower limit alarms for individual process parameters, lacking a comprehensive quantitative evaluation system covering the entire production line process, multiple areas, and multiple parameters. Consequently, it is impossible to make horizontal comparisons of the overall performance of different production lines, making it difficult for companies to identify their own production line's position in the industry and to scientifically quantify the overall performance of their production line's processes, equipment, control, operation, and management.

[0004] Second, there is a lack of quantitative scoring methods for root cause analysis. When defects occur in galvanized products (such as surface quality issues, uneven coating, zinc dross inclusions, etc.), existing systems struggle to quickly pinpoint whether the cause is a deviation in process parameters or an abnormal equipment condition. Furthermore, they lack a systematic root cause tracing capability based on quantitative scoring. Traditional problem-solving methods rely heavily on manual experience, resulting in lengthy and inefficient investigations, often requiring hours or even days to locate the root cause, severely impacting production efficiency and product quality stability.

[0005] Third, there is insufficient attention paid to equipment parameters. Existing technologies mainly focus on process parameters (such as temperature, concentration, and pressure), lacking a systematic mechanism for collecting and evaluating equipment condition parameters (such as brush roller wear, nozzle clogging, changes in roller surface roughness, and furnace roller coating condition). However, equipment condition is often the underlying cause of process deviations and product quality problems.

[0006] Fourth, some key parameters cannot be automatically collected. During the galvanizing process, some key parameters (such as roller marks, surface residues, plate shape defects, serrated edges, bulges, etc.) are difficult to collect automatically using conventional sensors. The existing system does not provide an effective manual input interface, resulting in the absence of this important information in the evaluation system and incomplete and inaccurate scoring results.

[0007] Therefore, there is an urgent need for a method and system that can simultaneously collect process and equipment parameters, support manual input, and achieve comprehensive scoring and automatic root cause diagnosis, so as to scientifically quantify the overall level of cold-rolled galvanizing production lines, quickly locate abnormal links, and support the further improvement of galvanized product quality and process management level. Summary of the Invention

[0008] In view of this, the purpose of the present invention is to provide a comprehensive scoring system and method for cold-rolled galvanizing production lines.

[0009] To achieve the above objectives, the present invention provides the following technical solution: In a first aspect, the present invention provides a comprehensive scoring system for a cold-rolled galvanized production line, comprising: The data acquisition module is used to acquire process and equipment parameters in real time for nine areas, including the inlet section, cleaning section, furnace area, zinc pot area, cooling tower, finishing machine, passivation, oiling, and packaging. The scoring rule library is used to store the total score for each region, the standards for each individual indicator, and their corresponding scores; The scoring calculation engine is used to compare the measured parameters with the scoring rule library to calculate the individual score, the actual score of the region, and the comprehensive score of the production line. The root cause diagnosis module is used to automatically locate low-scoring indicators when the score of any region or the overall score of the production line is lower than a preset threshold, trace the possible cause chain according to the root cause rule base, and output the diagnosis results and corrective measures. The scoring output module is used to generate scoring reports, comprehensive score curves, diagnostic results, and early warning information.

[0010] Furthermore, the key scoring items for the inlet section are quality information characterizing the incoming material, including: surface residue, thickness deviation, plate shape, roll shape, serrated edge, bulge, and roller mark.

[0011] Furthermore, the key scoring items for the cleaning section include whiteness after cleaning, effective alkali concentration, alkali temperature, electrolysis current, nozzle spraying status, brush roller pressure, and drying temperature, and take into account the nozzle cleaning and brush roller surface inspection cycle and whether a whiteness measuring instrument is used.

[0012] Furthermore, the key scoring items for the furnace area include slow cooling capacity, burner air-fuel ratio, residual oxygen content in exhaust gas, CO concentration in exhaust gas, furnace roller roughness, radiant tube material, furnace roller type, pipeline cleaning cycle, thermocouple high-temperature meter calibration cycle, and whether a tar removal device is used.

[0013] Furthermore, the key scoring items for the zinc pot area include Al concentration, Fe concentration, submerged roller preheating temperature, air knife height, zinc pot liquid level, zinc pot temperature uniformity, three-roller material, three-roller installation gap, humidifying nitrogen dew point and flow rate, humidifying nitrogen injection position, frequency and amount of production speed changes, zinc pot roller bearing material, submerged roller scraper operation, zinc boiler nose head replacement cycle, side baffle maintenance cycle, furnace nose camera maintenance cycle, Zn sampling location change cycle, zinc ingot acceptance standards, on-site operation standard revision status, and whether a pre-melting pot is set up.

[0014] Furthermore, the key evaluation items for the cooling tower include Fe concentration, nozzle cleaning cycle, water quenching tank filter maintenance cycle, channel roller surface cleaning cycle, top roller alignment, No. 2 roller scraper usage, and whether the top roller non-woven fabric and contact roller are installed.

[0015] Furthermore, the key scoring items for the finishing mill include elongation, high-pressure water pressure, finishing liquid injection position, roll roughness, filter and pipeline cleaning cycle, front and rear roll cleaning cycle of the finishing mill, maintenance status of the rear extrusion roll of the finishing mill, and whether an inspection deck is installed.

[0016] Furthermore, the key evaluation items for passivation include Cr adhesion amount, passivation film weight, passivation film thickness, oven temperature, Zn powder, condition of the coating machine scraper, surface cleanliness of the coating roller, and hygiene around the coating machine.

[0017] Furthermore, the key evaluation items for the oiling machine include the oiling amount measurement cycle, the moisture management in the oil tank, the cleaning and maintenance cycle of the blade and the oil tank, and whether a heater is installed.

[0018] Furthermore, the key scoring items for the packaging include surface roughness, frequency of adhesion tests, frequency of foreign matter inspection on the product surface before packaging, and whether a plastic pad is inserted when bundling the product packaging.

[0019] Furthermore, the data acquisition module includes an automatic acquisition submodule and a manual input submodule; The automatic acquisition submodule acquires real-time measurement values ​​on-site by collecting data from sensors and PLCs, and automatically acquires production data from upstream processes through a full-process data integration method. The manual input submodule is used to provide manual input functionality for parameters that cannot be automatically collected, allowing the input parameters to be modified and maintained.

[0020] Furthermore, the scoring rule library stores the total score for nine areas and the standard and score for each individual indicator, with the entrance section having a total score of 5 points, the cleaning section having a total score of 17 points, the furnace area having a total score of 13 points, the zinc pot area having a total score of 38 points, the cooling tower having a total score of 8 points, the finishing machine having a total score of 6 points, the passivation having a total score of 6 points, the oiling machine having a total score of 3 points, and the packaging having a total score of 4 points.

[0021] Furthermore, the scoring calculation engine is used to compare the measured parameters with the scoring rule library. If the collected data is within the scoring standard range, the corresponding score is directly taken; otherwise, 0 points are taken. For periodic maintenance information, if the maintenance cycle is less than the specified value or the maintenance frequency is greater than the specified value, the corresponding score is taken; otherwise, 0 points are taken. For setting items, if they exist, the corresponding score is taken; if they do not exist, 0 points are taken. By calculating the individual item scores and summing them, the scores for each region are obtained. The scores for each region are then added together to obtain the overall score of the production line.

[0022] Furthermore, the root cause diagnosis module includes: a root cause rule base, which stores the mapping relationship between each indicator and potential causes, and supports single-factor and multi-factor composite diagnosis; and an inference engine, which, based on the set of evaluation indicators, uses forward chain or decision tree algorithms to output the most likely cause ranking and suggested measures.

[0023] On the other hand, the present invention provides a comprehensive scoring method for a cold-rolled galvanizing production line based on the system, comprising the following steps: 1) Configure the scoring template and select the corresponding subset of scoring rules based on the specifications of the manufactured products; 2) The key parameters of each area are acquired at regular intervals through the data acquisition module. The process parameters and equipment parameters that are automatically acquired are read by sensors and PLCs, while the parameters that cannot be automatically acquired are input through the manual input sub-module. 3) The scoring engine compares each item against the standard and calculates the score for each item; 4) Summarize the actual scores for each region, and calculate the regional score and the overall score for the production line; 5) Determine if any regional score or production line overall score is below a preset threshold; if not, manually trigger or directly generate a normal scoring report; if yes, trigger step 6). 6) Automatic root cause diagnosis: Mark indicators with scores below the maximum score of a single item as abnormal indicators, match them with the root cause rule base, and the inference engine calculates and sorts the confidence of each potential cause, generating a diagnostic report containing a list of causes, confidence, and handling suggestions. 7) The scoring output module outputs a scoring report, a comprehensive score curve, and diagnostic results, and pushes early warning information.

[0024] The beneficial effects of this invention are as follows: it simultaneously collects process parameters and equipment parameters, covering all elements of production line operation; the manual input function solves the pain point that some parameters cannot be automatically collected, ensuring the completeness of the scoring; it scientifically quantifies the overall level of the production line, thereby understanding the current situation, identifying gaps, and promoting improvement; it automatically triggers root cause diagnosis through threshold warnings, significantly shortening fault diagnosis time (from hours to seconds); it supports composite factor diagnosis, avoiding misjudgment based on a single indicator; and it can be integrated with the MES system to achieve closed-loop quality control and intelligent process optimization, supporting further improvement in the quality and process management level of galvanized products.

[0025] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0026] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein: Figure 1 This is a diagram of the comprehensive scoring system architecture for a cold-rolled galvanized production line. Figure 2 The curves showing the changes in the overall score and key area score rate of a 1800mm cold-rolled galvanized production line over a continuous week are shown. Figure 3 This is the architecture diagram of the root cause diagnosis module. Detailed Implementation

[0027] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0028] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0029] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.

[0030] Example 1: like Figure 1 As shown, the present invention provides a comprehensive scoring system for a cold-rolled galvanized production line, comprising: Data Acquisition Module: This module includes an automatic acquisition submodule and a manual entry submodule. The automatic acquisition submodule connects to the production line PLC, zinc coating thickness gauge, thermometer, concentration analyzer, whiteness meter, etc., via protocols such as OPC and Modbus, acquiring process and equipment parameters every 10 seconds. The manual entry submodule provides a human-machine interface (HMI) or mobile terminal for entering parameters that cannot be automatically acquired, such as: laboratory test values ​​for "surface residue" at the inlet section, measurement values ​​for "serrated edge" at the inlet section, and handheld roughness tester values ​​for "roll roughness" on the finishing mill. Manual entry supports batch or scheduled task reminders, and entered data is timestamped and stored in the database.

[0031] Scoring rule library: Stores the total score for nine areas and the standard and score for each individual indicator. The total score for the entrance section is 5 points, the total score for the cleaning section is 17 points, the total score for the furnace area is 13 points, the total score for the zinc pot area is 38 points, the total score for the cooling tower is 8 points, the total score for the finishing machine is 6 points, the total score for passivation is 6 points, the total score for the oiling machine is 3 points, and the total score for packaging is 4 points.

[0032] Scoring Calculation Engine: The processor runs the scoring algorithm, assigning a score to each individual indicator (automatically collected data is scored in real time; manually entered data is scored according to the entry time), and calculates the actual score for the area and the overall score for the production line. Calculation Formula: Regional Score Rate = (Actual Regional Score / Total Regional Score) × 100% Production line overall score = Σ Actual score of each region like Figure 3 As shown, the root cause diagnosis module contains a root cause rule base and an inference engine. Diagnosis is triggered when the regional score rate is below 80% or the overall production line score is below 90. The thresholds for the regional score rate and the overall production line score are manually set in advance.

[0033] Scoring output module: Generates scoring dashboards, historical trend curves, diagnostic information, and pushes alerts to large screens or administrators' mobile phones.

[0034] Example 2: This embodiment provides some rules from the root cause rule base, as shown in Table 1.

[0035] Table 1

[0036] Example 3: like Figure 2 As shown, this embodiment provides the following practical application examples: Table 2 shows the data for one week from a certain 1800mm cold-rolled galvanized production line: Table 2

[0037] Example of automatic diagnostic output on March 12: Overall production line score: 79.6 (below the set threshold of 90) Abnormal area: Zinc pot area (score rate 68.0%) List of abnormal indicators: Al concentration: 0 points (actual measurement 0.17%, standard 0.22±0.02%) Air knife blade maintenance status: 0 points (partial blockage) Submerged roller scraper operation status: 0 points (not in operation) Furnace nose camera performance: 0.5 / 1 minute (blurry) Root cause analysis (confidence ranking): 1) Clogged air knife blade (confidence level 0.92): Stop the machine immediately and clean the blade.

[0038] 2) Al concentration deviation (confidence level 0.85): Check the aluminum ingot addition system, increase manual addition, and test Al every 2 hours.

[0039] 3) Submerged roller scraper failure (confidence level 0.78): Check cylinder pressure and replace scraper blade.

[0040] 4) Composite diagnosis: Slagging at the furnace nose (confidence level 0.72): Clean the furnace nose and adjust the humidifying N2 flow rate to 30±5 m³ / h.

[0041] Recommended priority order: ① Clean the air knife blade lip → ② Adjust the Al addition amount → ③ Check the scraper → ④ Clean the furnace nose.

[0042] Following the implementation of the diagnostic report on-site, the zinc pot area's score rate rebounded to 90.5% on March 13, and the overall production line score recovered to 91.3.

[0043] Example 4: This embodiment provides a case of manually entered data triggering a diagnosis. On March 15th, the manually entered value for "surface residue" at the inlet section was 520 mg / m² (standard value ≤ 450 mg / m²), resulting in a score of 0. The system automatically matched root cause rules and output a diagnosis: inadequate incoming material cleaning or insufficient brushing at the inlet section, suggesting checking the brush roller pressure and cleaning fluid concentration at the inlet section. The operator's inspection revealed that the brush roller current was only 8A (standard 10~15A). After adjusting it to 12A, the manually entered value dropped to 430 mg / m² on March 16th, and the score recovered.

[0044] Example 5: This embodiment provides a verification method for the effect of composite diagnosis.

[0045] On March 15th, both the furnace area score rate (85.0%) and the zinc pot area furnace nose camera malfunctioned. The inference engine matched rules R004 and R005, outputting a composite diagnosis: furnace roller wear + abnormal furnace atmosphere + furnace nose slagging. Recommended sequence: First, adjust the air-fuel ratio to reduce exhaust gas O2 from 3.5% to 1.5%, and the furnace area score rate should recover to 90.5% the next day; then, schedule a shutdown to clean the furnace nose and replace the furnace rollers, fully restoring the furnace to normal levels.

[0046] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A comprehensive scoring system for a cold-rolled galvanizing production line, characterized in that: include: The data acquisition module is used to acquire process and equipment parameters in real time for nine areas, including the inlet section, cleaning section, furnace area, zinc pot area, cooling tower, finishing machine, passivation, oiling, and packaging. The scoring rule library is used to store the total score for each region, the standards for each individual indicator, and their corresponding scores; The scoring calculation engine is used to compare the measured parameters with the scoring rule library to calculate the individual score, the actual score of the region, and the comprehensive score of the production line. The root cause diagnosis module is used to automatically locate low-scoring indicators when the score of any region or the overall score of the production line is lower than a preset threshold, trace the possible cause chain according to the root cause rule base, and output the diagnosis results and corrective measures. The scoring output module is used to generate scoring reports, comprehensive score curves, diagnostic results, and early warning information.

2. The comprehensive scoring system for a cold-rolled galvanized production line according to claim 1, characterized in that: The key scoring items for the inlet section are quality information characterizing the incoming material, including: surface residue, thickness deviation, plate shape, roll shape, serrated edge, bulge, and roller marks.

3. The comprehensive scoring system for a cold-rolled galvanized production line according to claim 1, characterized in that: The key scoring items for the cleaning section include whiteness after cleaning, effective alkali concentration, alkali temperature, electrolysis current, nozzle spraying status, brush roller pressure, and drying temperature, and take into account the nozzle cleaning and brush roller surface inspection cycle and whether a whiteness meter is used.

4. The comprehensive scoring system for a cold-rolled galvanized production line according to claim 1, characterized in that: The key evaluation items for the furnace area include slow cooling capacity, burner air-fuel ratio, residual oxygen content in exhaust gas, CO concentration in exhaust gas, furnace roller roughness, radiant tube material, furnace roller type, pipeline cleaning cycle, thermocouple high-temperature meter calibration cycle, and whether a tar removal device is used.

5. The comprehensive scoring system for a cold-rolled galvanized production line according to claim 1, characterized in that: Key scoring items for the zinc pot area include Al concentration, Fe concentration, submerged roller preheating temperature, air knife height, zinc pot liquid level, zinc pot temperature uniformity, three-roller material, three-roller installation gap, humidifying nitrogen dew point and flow rate, humidifying nitrogen injection location, frequency and amount of production speed changes, zinc pot roller bearing material, submerged roller scraper operation, zinc boiler nose replacement cycle, side baffle maintenance cycle, furnace nose camera maintenance cycle, Zn sampling location change cycle, zinc ingot acceptance standards, on-site operation standard revision status, and whether a pre-melting pot is set up.

6. The comprehensive scoring system for a cold-rolled galvanized production line according to claim 1, characterized in that: The key scoring items for the cooling tower include Fe concentration, nozzle cleaning cycle, water quenching tank filter maintenance cycle, channel roller surface cleaning cycle, top roller alignment, No. 2 roller scraper usage, and whether the top roller non-woven fabric and contact roller are installed.

7. The comprehensive scoring system for a cold-rolled galvanized production line according to claim 1, characterized in that: The key scoring items for the finishing mill include elongation, high-pressure water pressure, finishing liquid injection position, roll roughness, filter and pipeline cleaning cycle, front and rear roll cleaning cycle of the finishing mill, maintenance status of the rear extrusion roll of the finishing mill, and whether an inspection deck is installed.

8. The comprehensive scoring system for a cold-rolled galvanized production line according to claim 1, characterized in that: The key evaluation items for passivation include Cr adhesion amount, passivation film weight, passivation film thickness, oven temperature, Zn powder, condition of the coating machine scraper, surface cleanliness of the coating roller, and hygiene around the coating machine.

9. The comprehensive scoring system for a cold-rolled galvanized production line according to claim 1, characterized in that: The key evaluation criteria for the oiling machine include the oiling amount measurement cycle, the moisture management in the oil tank, the cleaning and maintenance cycle of the blade and oil tank, and whether a heater is installed.

10. The comprehensive scoring system for a cold-rolled galvanized production line according to claim 1, characterized in that: The key scoring items for the packaging include surface roughness, frequency of adhesion tests, frequency of foreign matter inspection on the product surface before packaging, and whether plastic pads are inserted when bundling the product packaging.

11. The comprehensive scoring system for a cold-rolled galvanized production line according to claim 1, characterized in that: The data acquisition module includes an automatic acquisition submodule and a manual input submodule; The automatic acquisition submodule acquires real-time measurement values ​​on-site by collecting data from sensors and PLCs, and automatically acquires production data from upstream processes through a full-process data integration method. The manual input submodule is used to provide manual input functionality for parameters that cannot be automatically collected, allowing the input parameters to be modified and maintained.

12. The comprehensive scoring system for a cold-rolled galvanized production line according to claim 1, characterized in that: The scoring rule base stores the total score for nine areas and the standard and score for each individual indicator, with the entrance section having a total score of 5 points, the cleaning section having a total score of 17 points, the furnace area having a total score of 13 points, the zinc pot area having a total score of 38 points, the cooling tower having a total score of 8 points, the finishing machine having a total score of 6 points, the passivation having a total score of 6 points, the oiling machine having a total score of 3 points, and the packaging having a total score of 4 points.

13. The comprehensive scoring system for a cold-rolled galvanized production line according to claim 1, characterized in that: The scoring calculation engine compares the measured parameters with the scoring rule library. If the collected data is within the scoring standard range, the corresponding score is directly taken; otherwise, 0 points are taken. For periodic maintenance information, if the maintenance cycle is less than the specified value or the maintenance frequency is greater than the specified value, the corresponding score is taken; otherwise, 0 points are taken. For setting items, if they exist, the corresponding score is taken; otherwise, 0 points are taken. The scores for each area are obtained by calculating the individual item scores and summing them up. The comprehensive score of the production line is obtained by adding the scores of each area.

14. The comprehensive scoring system for a cold-rolled galvanized production line according to claim 1, characterized in that: The root cause diagnosis module includes: a root cause rule base, which stores the mapping relationship between each indicator and potential causes, and supports single-factor and multi-factor composite diagnosis; and an inference engine, which, based on the set of evaluation indicators, uses forward chain or decision tree algorithms to output the most likely cause ranking and suggested measures.

15. A comprehensive scoring method for a cold-rolled galvanizing production line based on the system described in any one of claims 1 to 14, characterized in that: Includes the following steps: 1) Configure the scoring template and select the corresponding subset of scoring rules based on the specifications of the manufactured products; 2) The key parameters of each area are acquired at regular intervals through the data acquisition module. The process parameters and equipment parameters that are automatically acquired are read by sensors and PLCs, while the parameters that cannot be automatically acquired are input through the manual input sub-module. 3) The scoring engine compares each item against the standard and calculates the score for each item; 4) Summarize the actual scores for each region, and calculate the regional score and the overall score for the production line; 5) Determine if any regional score or production line overall score is below a preset threshold; if not, manually trigger or directly generate a normal scoring report; if yes, trigger step 6). 6) Automatic root cause diagnosis: Mark indicators with scores below the maximum score of a single item as abnormal indicators, match them with the root cause rule base, and the inference engine calculates and sorts the confidence of each potential cause, generating a diagnostic report containing a list of causes, confidence, and handling suggestions. 7) The scoring output module outputs a scoring report, a comprehensive score curve, and diagnostic results, and pushes early warning information.

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