A Cleaner Production Evaluation Method Based on AHP in the Slag Powder Manufacturing Industry

Abstract

This invention discloses a cleaner production evaluation method for the slag powder manufacturing industry based on Analytic Hierarchy Process (AHP), comprising the following steps: formulating an evaluation scheme, collecting and organizing data, constructing an evaluation index system, determining the data collection cycle and sample size, determining data collection points and frequency, data collection and processing, selecting testing methods / analytic hierarchy process (AHP) weight calculation, and comprehensive evaluation of cleaner production levels. This invention constructs a primary index covering nine dimensions: production processes and equipment, energy consumption, water consumption, raw / auxiliary material consumption, comprehensive resource utilization, pollutant generation and emissions, greenhouse gas emissions, product characteristics, and cleaner production management. Each index is further divided into several secondary indicators. Based on a coupled model of AHP and expert consultation, the comprehensive weight of each evaluation index is determined; based on production data, evaluation indicators, and corresponding weights, the cleaner production level of enterprises is quantitatively or qualitatively evaluated; the cleaner production level of enterprises is determined, and targeted optimization suggestions are proposed.

Description

Technical Field

[0001] This invention relates to the technical field of clean production evaluation methods in the slag powder manufacturing industry, and particularly to a clean production evaluation method based on AHP in the slag powder manufacturing industry. Background Technology

[0002] Slag powder, as a new type of green building material, can effectively utilize waste slag from steel smelting and replace some cement, making it widely used in the construction industry. my country's slag powder industry has developed rapidly, with a national production capacity reaching 182 million tons in 2023. Shaanxi Province accounts for 52% of the production capacity in Northwest China, making it a regional specialty industry. However, the slag powder industry is a high-energy-consuming industry, facing challenges such as high energy consumption, uneven resource utilization efficiency, and difficulty in controlling pollutant emissions during production.

[0003] Currently, neither the national nor local governments have formulated specific clean production evaluation standards for the slag powder industry, and existing evaluation methods have several shortcomings: First, the evaluation indicators lack systematicity, often focusing on a single dimension and failing to cover the entire production process; second, the methods for determining weights are simplistic, highly subjective, or overly reliant on data statistics, making it difficult to balance expert experience with objective reality; third, the evaluation process lacks standardized and quantitative methods, making it difficult to compare clean production levels across different enterprises; fourth, it does not fully consider industry-specific indicators, such as key parameters like steel slag utilization rate and iron recovery rate, resulting in weakly targeted evaluation results. Furthermore, existing methods often fail to incorporate carbon emissions into the evaluation system.

[0004] Therefore, there is an urgent need for a comprehensive, scientifically weighted, and accurate evaluation method for clean production in the slag powder manufacturing industry, in order to standardize the industry's clean production audit work, guide enterprises to save energy and reduce pollution and increase efficiency, and promote the green upgrading of the industry. Summary of the Invention

[0005] This invention provides a clean production evaluation method for the slag powder manufacturing industry based on AHP, in order to solve the technical problems existing in the prior art.

[0006] To achieve the above objectives, this invention provides a clean production evaluation method for the slag powder manufacturing industry based on AHP, which includes:

[0007] S1: Develop an evaluation plan, clarifying the evaluation purpose, scope, and content;

[0008] S2: Collect technical information and data from slag powder enterprises, and collect and organize the data;

[0009] S3: Based on the characteristics of the slag powder manufacturing industry, determine the specific content and calculation method of the evaluation index system, and construct an evaluation index system covering nine dimensions: production process and equipment, energy consumption, water consumption, raw / auxiliary material consumption, comprehensive resource utilization, pollutant generation and emission, greenhouse gas emission, product characteristics, and cleaner production management.

[0010] S4: Determine the evaluation data collection cycle and sample size. Based on the above information, determine the evaluation data collection cycle and sample size to ensure that the data collection can fully reflect the company's clean production level.

[0011] S5: Determine the location and number of data collection points and the data collection frequency based on the slag powder production process, technical characteristics, and existing data to meet the requirements for data collection of different indicators within the evaluation period.

[0012] S6: Collect and test the following data in accordance with relevant standards and specifications: production process parameters, energy consumption, water consumption, raw and auxiliary material consumption, comprehensive utilization of resources, pollutant generation and emission, greenhouse gas emission, and product quality;

[0013] S7: Establish a hierarchical structure, decompose the evaluation indicators into target layer, criterion layer and indicator layer from top to bottom, select appropriate scale to construct judgment matrix, and use the analytic hierarchy process combined with expert consultation to determine the weight of each level of indicator;

[0014] S8: Based on the evaluation index system and weight calculation results, conduct a comprehensive evaluation of the clean production level of slag powder manufacturing enterprises and determine the clean production level of the enterprises.

[0015] In one embodiment of the present invention, optionally, step S2, when collecting and organizing data, includes the following steps:

[0016] S21: Collect all relevant information about slag powder enterprises, including basic enterprise information, production process flow, equipment list, energy consumption data, raw and auxiliary material consumption data, product output and quality data, environmental protection facility operation status, environmental monitoring data, and clean production management system, to ensure the data foundation for the evaluation work;

[0017] S22: Systematically organize and analyze the collected data, extract key information, and verify the authenticity and reliability of the data;

[0018] S23: Based on the evaluation requirements, compile a list of technical data to be collected, specifying the types, quantities, and sources of the required data, and ensuring the completeness and systematic nature of the data collection.

[0019] In one embodiment of the present invention, optionally, step S3, when constructing the evaluation index system, includes the following steps:

[0020] S31: Conduct in-depth research on the characteristics of the slag powder manufacturing industry, including production process flow, main equipment types, energy consumption structure, raw and auxiliary material characteristics, and product application fields, to provide a basis for the construction of the evaluation index system;

[0021] S32: Based on industry characteristics, construct an evaluation indicator system framework covering nine dimensions: production process and equipment, energy consumption, water consumption, raw / auxiliary material consumption, comprehensive resource utilization, pollutant generation and emission, greenhouse gas emission, product characteristics, and cleaner production management, and clarify the specific content and hierarchical structure of evaluation indicators at each level.

[0022] The production process and equipment indicators include: raw material storage and transportation methods, single mill scale, mill type, product storage and transportation methods, steel slag ratio in raw materials, heat source for drying, energy-saving motor load, metering equipment status, and the percentage of noise reduction measures adopted for major noise sources.

[0023] The energy consumption indicators include: electricity consumption per unit product process, fuel consumption per unit product, and comprehensive energy consumption per unit product.

[0024] The water resource consumption indicators include: fresh water consumption per unit product and comprehensive utilization rate of industrial wastewater.

[0025] The raw / auxiliary material consumption indicators include: raw material moisture content, raw material sulfur content, and raw material iron content entering the mill.

[0026] The comprehensive resource utilization indicators include: iron recovery rate;

[0027] The pollutant generation and emission indicators include: particulate matter emission per unit product and the installation of leachate collection facilities.

[0028] The greenhouse gas emission indicators include: carbon emissions per unit product;

[0029] The product characteristic indicators include: product quality;

[0030] The clean production management indicators include: compliance with environmental laws and regulations, industrial policy compliance, environmental management agencies and personnel, pollutant emission monitoring, establishment and improvement of environmental management system and energy management system, clean production audit, transportation methods and transportation supervision;

[0031] S33: Develop specific calculation methods for evaluation indicators at all levels, including calculation formulas for quantitative indicators and evaluation standards for qualitative indicators, to ensure the accuracy and repeatability of evaluation results;

[0032] S34: Based on industrial policies and cleaner production requirements, determine limiting indicators, including raw material storage and transportation methods, product storage and transportation methods, unit product process power consumption, unit product fuel consumption, unit product comprehensive energy consumption, industrial wastewater comprehensive utilization rate, unit product particulate matter emissions, environmental protection laws and regulations compliance, industrial policy compliance, and cleaner production audit.

[0033] In one embodiment of the present invention, optionally, step S4, when determining the evaluation data collection period and sample size, includes the following steps:

[0034] S41: Collect detailed information on the production process of slag powder, equipment operating parameters, raw and auxiliary material characteristics, product specifications, energy consumption structure, and pollutant emission characteristics to provide a basis for determining the data collection cycle and sample size;

[0035] S42: Based on the evaluation objectives and indicators, analyze the specific requirements for data collection cycle and sample size to ensure that data collection can fully reflect the company's clean production level. The assessment cycle is based on a production year and is synchronized with the production year.

[0036] S43: Based on the analysis results and in accordance with relevant standards and specifications, determine the specific data collection cycle and sample size to ensure the scientific rigor and rationality of the data collection work.

[0037] In one embodiment of the present invention, optionally, step S5, when determining the data acquisition points and data acquisition frequency, includes the following steps:

[0038] S51: Conduct in-depth research on the production process and technical characteristics of slag powder, and clarify the requirements for setting up data collection points and the specific needs for data collection frequency;

[0039] S52: Based on the analysis results, combined with the actual situation of the enterprise and the evaluation criteria, determine the specific locations and number of data collection points to ensure the comprehensiveness and representativeness of the data collection work;

[0040] S53: Based on the evaluation cycle and data collection requirements, formulate a specific data collection frequency plan, clarify the data collection time and number of collections for different indicators, and ensure the accuracy and reliability of the data.

[0041] In one embodiment of the present invention, optionally, when collecting and testing data in step S6, the following steps are included:

[0042] S61: Prepare the appropriate data collection tools and equipment according to the data collection requirements to ensure the smooth progress of the data collection work;

[0043] S62: In accordance with relevant standards and specifications, conduct on-site data collection or testing on production process parameters, energy consumption, water consumption, raw and auxiliary material consumption, comprehensive resource utilization, pollutant generation and emission, greenhouse gas emission, and product quality to ensure the accuracy and representativeness of the data;

[0044] S63: Properly process and store the collected data to avoid data loss and errors during processing and storage, and ensure the integrity and accuracy of the data.

[0045] In one embodiment of the present invention, optionally, when testing the data in step S6, the following steps are included:

[0046] S61′: Comprehensively collect existing national or industry standard methods, and understand the applicable scope and specific operating procedures of various testing methods;

[0047] S62′: Based on the evaluation objectives and evaluation indicators, analyze the specific requirements of the testing methods and select appropriate testing methods;

[0048] S63′: Verify the selected test method to ensure its accuracy and reliability. If there is no existing standard method, the testing organization shall develop its own test method and conduct necessary methodological verification.

[0049] In one embodiment of the present invention, optionally, when using the analytic hierarchy process (AHP) to calculate weights, the following steps are included:

[0050] S71: Decompose the evaluation indicators from top to bottom into the target layer, criterion layer and indicator layer to construct a hierarchical structure model;

[0051] The target layer is the comprehensive evaluation index for clean production in the slag powder manufacturing industry.

[0052] The criteria layer consists of nine primary indicators: production process and equipment, energy consumption, water consumption, raw / auxiliary material consumption, comprehensive resource utilization, pollutant generation and emission, greenhouse gas emission, product characteristics, and cleaner production management.

[0053] The indicator layer consists of the secondary indicators under each primary indicator;

[0054] S72: Select an appropriate scale, use the 1-9 scale method, and construct the judgment matrix for each level according to the actual situation;

[0055] S73: Use Matlab to solve for the eigenvectors and eigenvalues ​​of the judgment matrix, and calculate the weights of each evaluation index;

[0056] The weights of the primary indicators were determined using a combination of the analytic hierarchy process (AHP) and expert consultation. Specifically:

[0057] Weighting of production process and equipment indicators: 0.24

[0058] Energy consumption indicator weight: 0.12

[0059] Water resource consumption index weight: 0.06

[0060] Weight of raw / auxiliary material resource consumption index: 0.07

[0061] Weight of resource comprehensive utilization index: 0.08

[0062] Pollutant generation and emission index weight: 0.13

[0063] Greenhouse gas emission indicator weight: 0.10

[0064] Product feature index weight: 0.06

[0065] Clean production management indicator weight: 0.14

[0066] S74: Calculate the consistency index CR of the judgment matrix according to the consistency test formula to ensure that the consistency of the judgment matrix meets the requirements. When CR > 0.1, the judgment matrix needs to be corrected until the result meets the consistency test requirements.

[0067] S75: Compile the weight calculation results of each evaluation indicator into a table to provide a basis for subsequent comprehensive evaluation.

[0068] In one embodiment of the present invention, optionally, step S7, which uses the analytic hierarchy process (AHP) combined with expert consultation to determine the weights of each level of indicators, includes:

[0069] Using the analytic hierarchy process (AHP), more than 10 environmental experts, industry experts, and cleaner production experts were invited to compare the relative importance of each evaluation indicator pairwise. A judgment matrix was constructed using the 1-9 scale method. The consistency of the matrix was tested by the consistency ratio (CR). When the CR was less than 0.1, the eigenvectors were normalized, and the subjective weights of each evaluation indicator were calculated.

[0070] The production data is standardized, extreme data is removed, the information entropy of each evaluation indicator is calculated, and the objective weight is calculated based on the information entropy.

[0071] Determine the weighting coefficients The comprehensive weight of each evaluation index is calculated using a linear weighting method. The calculation formula is as follows:

[0072]

[0073] in, The comprehensive weight of the j-th evaluation indicator is... Let j be the subjective weight of the j-th evaluation indicator. Let be the objective weight of the j-th evaluation indicator.

[0074] In one embodiment of the present invention, optionally, step S8, when comprehensively evaluating the clean production level of slag powder manufacturing enterprises, includes:

[0075] S81: Based on the evaluation index system and weight calculation results, collect specific data for each evaluation index, including production process and equipment index, energy consumption index, water resource consumption index, raw / auxiliary material resource consumption index, comprehensive resource utilization index, pollutant generation and emission index, greenhouse gas emission index, product characteristic index, and cleaner production management index.

[0076] S82: Dimensionless processing is performed on the secondary indicators, membership functions of the original indicators are established, and the comprehensive evaluation index score is calculated using a weighted average and step-by-step convergence method.

[0077] S83: Based on the comprehensive evaluation index score and the compliance status of the limiting indicators, determine the clean production level of the slag powder manufacturing enterprise, and prepare a clean production evaluation report, which elaborates on the evaluation process, results and recommendations.

[0078] The method for determining the clean production level is as follows:

[0079] Level I represents the advanced / benchmark level of clean production: all restrictive indicators meet the Level I benchmark requirements, the comprehensive evaluation index score YⅠ≥85 points, and all non-restrictive indicators meet the Level II benchmark requirements;

[0080] Level II represents the clean production access level: all restrictive indicators meet the Level II benchmark requirements, the comprehensive evaluation index score YⅡ≥85 points, and all non-restrictive indicators meet the Level III benchmark requirements.

[0081] Level III represents the general level of clean production: all limiting indicators meet the Level III benchmark requirements, and the comprehensive evaluation index score YⅢ=100 points;

[0082] Clean production requirements not met: The Level III limiting indicators are not met or the comprehensive evaluation index score YⅢ is less than 100.

[0083] The clean production evaluation method for the slag powder manufacturing industry based on AHP provided by this invention overcomes the shortcomings of existing evaluation methods, such as strong subjectivity and insufficient data support, through a multi-dimensional index system and scientific weight determination method. It achieves a systematic and accurate assessment of the clean production level of slag powder enterprises, providing technical support for the green upgrading of the industry. In summary, this invention has the following beneficial technical effects:

[0084] By constructing a system of nine primary indicators and 29 secondary indicators covering the entire production process, including 10 limiting indicators, the system comprehensively covers the core aspects of slag powder production, thus solving the problem of the one-sidedness of existing evaluation indicators.

[0085] The weights are determined by coupling the AHP method and the Delphi method, which takes into account both expert experience and makes full use of the objective laws of data. The balance between subjective and objective factors is achieved by adjusting the weight coefficients, thereby improving the scientific nature of the weight determination.

[0086] Establish a standardized and quantitative evaluation process, combining a proprietary accounting formula and a tiered evaluation standard to achieve horizontal comparisons between different enterprises and vertical monitoring of the enterprises themselves, resulting in accurate and reliable evaluation results;

[0087] It generates targeted optimization suggestions, such as adopting a dual-fan system to reduce energy consumption and replacing permanent magnet motors to improve energy efficiency, providing clear guidance for enterprises to carry out clean production transformation and helping the industry achieve the green development goals of energy conservation, emission reduction and efficiency improvement. Attached Figure Description

[0088] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0089] Figure 1 This is a flowchart of a clean production evaluation method for the slag powder manufacturing industry based on AHP, according to an embodiment of the present invention.

[0090] Figure 2 This is a schematic diagram of the weight determination process in another embodiment of the present invention. Detailed Implementation

[0091] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0092] The Analytic Hierarchy Process (AHP) is a decision-making method that combines qualitative and quantitative approaches, breaks down complex decision problems into hierarchical structures, and calculates weights through pairwise comparisons. It is often used for optimal solution selection, weighting of evaluation indicators, and risk assessment.

[0093] Figure 1This is a flowchart of a clean production evaluation method for the slag powder manufacturing industry based on AHP, according to an embodiment of the present invention. Figure 1 As shown, this invention provides a clean production evaluation method for the slag powder manufacturing industry based on AHP, which includes:

[0094] S1: Develop an evaluation plan, clarifying the evaluation purpose, scope, and content;

[0095] S2: Collect technical information and data from slag powder enterprises, and collect and organize the data;

[0096] S3: Based on the characteristics of the slag powder manufacturing industry, determine the specific content and calculation method of the evaluation index system, and construct an evaluation index system covering nine dimensions: production process and equipment, energy consumption, water consumption, raw / auxiliary material consumption, comprehensive resource utilization, pollutant generation and emission, greenhouse gas emission, product characteristics, and cleaner production management.

[0097] S4: Determine the evaluation data collection cycle and sample size. Based on the above information, determine the evaluation data collection cycle and sample size to ensure that the data collection can fully reflect the company's clean production level.

[0098] S5: Determine the location and number of data collection points and the data collection frequency based on the slag powder production process, technical characteristics, and existing data to meet the requirements for data collection of different indicators within the evaluation period.

[0099] S6: Collect and test the following data in accordance with relevant standards and specifications: production process parameters, energy consumption, water consumption, raw and auxiliary material consumption, comprehensive utilization of resources, pollutant generation and emission, greenhouse gas emission, and product quality;

[0100] S7: Establish a hierarchical structure, decompose the evaluation indicators from top to bottom into the target layer, criterion layer and indicator layer, select an appropriate scale to construct a judgment matrix, and use the analytic hierarchy process (AHP) combined with the expert consultation method (Delphi method) to determine the weight of each level of indicator.

[0101] S8: Based on the evaluation index system and weight calculation results, conduct a comprehensive evaluation of the clean production level of slag powder manufacturing enterprises and determine the clean production level of the enterprises.

[0102] In one embodiment of the present invention, step S1 may optionally include:

[0103] S11: Determine the specific objectives for conducting a clean production assessment in the slag powder manufacturing industry, including evaluating the enterprise's clean production level, resource utilization efficiency, pollutant emission control, and carbon emissions.

[0104] S12: Define the geographical scope, time frame, and specific evaluation indicators involved in the evaluation to ensure the comprehensiveness and relevance of the evaluation work;

[0105] S13: Clearly define the specific responsibilities and division of tasks among the evaluation agency, testing agency, and the client who commissions the evaluation, to ensure the smooth progress of the evaluation work;

[0106] S14: Prepare a detailed evaluation plan, including an introduction to the company overview, a description of the production process, an evaluation indicator system, an evaluation work plan, quality assurance and quality control, a budget and schedule, to provide comprehensive guidance and basis for the evaluation work.

[0107] In one embodiment of the present invention, optionally, step S2 includes:

[0108] Collect full-process production data from slag powder enterprises to establish a clean production basic database. The production data includes production process parameters, energy consumption data, water resource consumption data, raw and auxiliary material consumption data, comprehensive resource utilization data, pollutant emission data, greenhouse gas emission data, product characteristic data, and clean production management data.

[0109] Specifically, production data forms the basis of clean production assessments. This requires collecting data from the entire production process of slag powder enterprises through a combination of enterprise statistics, on-site measurements, and online monitoring. This data includes production process and equipment parameters (such as the scale of a single mill, mill type, and heat source for drying), energy consumption data (electricity consumption per unit product, fuel consumption, and overall energy consumption), water resource consumption data (fresh water consumption per unit product, industrial wastewater discharge and reuse), raw / auxiliary material resource consumption data (moisture content of raw materials, sulfur content, iron content, etc.), comprehensive resource utilization data (iron recovery rate, etc.), pollutant generation and emission data (particulate matter emissions per unit product, leachate collection, etc.), greenhouse gas emission data (carbon emissions per unit product, etc.), product characteristic data (product quality compliance, etc.), and clean production management data (compliance with environmental laws and regulations, etc.). Based on the collected data, a tiered update mechanism should be established to ensure data timeliness and accuracy.

[0110] In one embodiment of the present invention, optionally, step S2, when collecting and organizing data, includes the following steps:

[0111] S21: Collect all relevant information about slag powder enterprises, including basic enterprise information, production process flow, equipment list, energy consumption data, raw and auxiliary material consumption data, product output and quality data, environmental protection facility operation status, environmental monitoring data, and clean production management system, to ensure the data foundation for the evaluation work;

[0112] S22: Systematically organize and analyze the collected data, extract key information, and verify the authenticity and reliability of the data;

[0113] S23: Based on the evaluation requirements, compile a list of technical data to be collected, specifying the types, quantities, and sources of the required data, and ensuring the completeness and systematic nature of the data collection.

[0114] In one embodiment of the present invention, optionally, step S3, when constructing the evaluation index system, includes the following steps:

[0115] S31: Conduct in-depth research on the characteristics of the slag powder manufacturing industry, including production process flow, main equipment types, energy consumption structure, raw and auxiliary material characteristics, and product application fields, to provide a basis for the construction of the evaluation index system;

[0116] S32: Based on industry characteristics, construct an evaluation indicator system framework covering nine dimensions: production process and equipment, energy consumption, water consumption, raw / auxiliary material consumption, comprehensive resource utilization, pollutant generation and emission, greenhouse gas emission, product characteristics, and cleaner production management, and clarify the specific content and hierarchical structure of evaluation indicators at each level.

[0117] The production process and equipment indicators include: raw material storage and transportation methods, single mill scale, mill type, product storage and transportation methods, steel slag ratio in raw materials, heat source for drying, energy-saving motor load, metering equipment status, and the percentage of noise reduction measures adopted for major noise sources.

[0118] The energy consumption indicators include: electricity consumption per unit product process, fuel consumption per unit product, and comprehensive energy consumption per unit product.

[0119] The water resource consumption indicators include: fresh water consumption per unit product and comprehensive utilization rate of industrial wastewater.

[0120] The raw / auxiliary material consumption indicators include: raw material moisture content, raw material sulfur content, and raw material iron content entering the mill.

[0121] The comprehensive resource utilization indicators include: iron recovery rate;

[0122] The pollutant generation and emission indicators include: particulate matter emission per unit product and the installation of leachate collection facilities.

[0123] The greenhouse gas emission indicators include: carbon emissions per unit product;

[0124] The product characteristic indicators include: product quality;

[0125] The clean production management indicators include: compliance with environmental laws and regulations, industrial policy compliance, environmental management agencies and personnel, pollutant emission monitoring, establishment and improvement of environmental management system and energy management system, clean production audit, transportation methods and transportation supervision;

[0126] S33: Develop specific calculation methods for evaluation indicators at all levels, including calculation formulas for quantitative indicators and evaluation standards for qualitative indicators, to ensure the accuracy and repeatability of evaluation results;

[0127] S34: Based on industrial policies and cleaner production requirements, determine limiting indicators, including raw material storage and transportation methods, product storage and transportation methods, unit product process power consumption, unit product fuel consumption, unit product comprehensive energy consumption, industrial wastewater comprehensive utilization rate, unit product particulate matter emissions, environmental protection laws and regulations compliance, industrial policy compliance, and cleaner production audit.

[0128] In one embodiment of the present invention, optionally, step S4, when determining the evaluation data collection period and sample size, includes the following steps:

[0129] S41: Collect detailed information on the production process of slag powder, equipment operating parameters, raw and auxiliary material characteristics, product specifications, energy consumption structure, and pollutant emission characteristics to provide a basis for determining the data collection cycle and sample size;

[0130] S42: Based on the evaluation objectives and indicators, analyze the specific requirements for data collection cycle and sample size to ensure that data collection can fully reflect the company's clean production level. The assessment cycle is based on a production year and is synchronized with the production year.

[0131] S43: Based on the analysis results and in accordance with relevant standards and specifications, determine the specific data collection cycle and sample size to ensure the scientific rigor and rationality of the data collection work.

[0132] In one embodiment of the present invention, optionally, step S5, when determining the data acquisition points and data acquisition frequency, includes the following steps:

[0133] S51: Conduct in-depth research on the production process and technical characteristics of slag powder, and clarify the requirements for setting up data collection points and the specific needs for data collection frequency;

[0134] S52: Based on the analysis results, combined with the actual situation of the enterprise and the evaluation criteria, determine the specific locations and number of data collection points to ensure the comprehensiveness and representativeness of the data collection work;

[0135] S53: Based on the evaluation cycle and data collection requirements, formulate a specific data collection frequency plan, clarify the data collection time and number of collections for different indicators, and ensure the accuracy and reliability of the data.

[0136] In one embodiment of the present invention, optionally, when collecting and testing data in step S6, the following is included:

[0137] S61: Prepare the appropriate data collection tools and equipment according to the data collection requirements to ensure the smooth progress of the data collection work;

[0138] S62: In accordance with relevant standards and specifications, conduct on-site data collection or testing on production process parameters, energy consumption, water consumption, raw and auxiliary material consumption, comprehensive resource utilization, pollutant generation and emission, greenhouse gas emission, and product quality to ensure the accuracy and representativeness of the data;

[0139] S63: Properly process and store the collected data to avoid data loss and errors during processing and storage, and ensure the integrity and accuracy of the data.

[0140] In one embodiment of the present invention, optionally, when testing the data in step S6, the following steps are included:

[0141] S61′: Comprehensively collect existing national or industry standard methods, and understand the applicable scope and specific operating procedures of various testing methods;

[0142] S62′: Based on the evaluation objectives and evaluation indicators, analyze the specific requirements of the testing methods and select appropriate testing methods;

[0143] S63′: Verify the selected test method to ensure its accuracy and reliability. If there is no existing standard method, the testing organization shall develop its own test method and conduct necessary methodological verification.

[0144] In one embodiment of the present invention, optionally, when using the analytic hierarchy process (AHP) to calculate weights, the following steps are included:

[0145] S71: Decompose the evaluation indicators from top to bottom into the target layer, criterion layer and indicator layer to construct a hierarchical structure model;

[0146] The target layer is the comprehensive evaluation index for clean production in the slag powder manufacturing industry.

[0147] The criteria layer consists of nine primary indicators: production process and equipment, energy consumption, water consumption, raw / auxiliary material consumption, comprehensive resource utilization, pollutant generation and emission, greenhouse gas emission, product characteristics, and cleaner production management.

[0148] The indicator layer consists of the secondary indicators under each primary indicator;

[0149] S72: Select an appropriate scale, use the 1-9 scale method, and construct the judgment matrix for each level according to the actual situation;

[0150] S73: Use Matlab to solve for the eigenvectors and eigenvalues ​​of the judgment matrix, and calculate the weights of each evaluation index;

[0151] The weights of the primary indicators were determined using a combination of the analytic hierarchy process (AHP) and expert consultation. Specifically:

[0152] Weighting of production process and equipment indicators: 0.24

[0153] Energy consumption indicator weight: 0.12

[0154] Water resource consumption index weight: 0.06

[0155] Weight of raw / auxiliary material resource consumption index: 0.07

[0156] Weight of resource comprehensive utilization index: 0.08

[0157] Pollutant generation and emission index weight: 0.13

[0158] Greenhouse gas emission indicator weight: 0.10

[0159] Product feature index weight: 0.06

[0160] Clean production management indicator weight: 0.14

[0161] S74: Calculate the consistency index CR of the judgment matrix according to the consistency test formula to ensure that the consistency of the judgment matrix meets the requirements. When CR > 0.1, the judgment matrix needs to be corrected until the result meets the consistency test requirements.

[0162] S75: Compile the weight calculation results of each evaluation indicator into a table to provide a basis for subsequent comprehensive evaluation.

[0163] In one embodiment of the present invention, optionally, step S7, which uses the analytic hierarchy process (AHP) combined with expert consultation to determine the weights of each level of indicators, includes:

[0164] Using the analytic hierarchy process (AHP), more than 10 environmental experts, industry experts, and cleaner production experts were invited to compare the relative importance of each evaluation indicator pairwise. A judgment matrix was constructed using the 1-9 scale method. The consistency of the matrix was tested by the consistency ratio (CR). When the CR was less than 0.1, the eigenvectors were normalized, and the subjective weights of each evaluation indicator were calculated.

[0165] The production data is standardized, extreme data is removed, the information entropy of each evaluation indicator is calculated, and the objective weight is calculated based on the information entropy.

[0166] Determine the weighting coefficients The comprehensive weight of each evaluation index is calculated using a linear weighting method. The calculation formula is as follows:

[0167]

[0168] in, The comprehensive weight of the j-th evaluation indicator is... Let j be the subjective weight of the j-th evaluation indicator. Let be the objective weight of the j-th evaluation indicator.

[0169] In one embodiment of the present invention, optionally, step S8, when comprehensively evaluating the clean production level of slag powder manufacturing enterprises, includes:

[0170] S81: Based on the evaluation index system and weight calculation results, collect specific data for each evaluation index, including production process and equipment index, energy consumption index, water resource consumption index, raw / auxiliary material resource consumption index, comprehensive resource utilization index, pollutant generation and emission index, greenhouse gas emission index, product characteristic index, and cleaner production management index.

[0171] S82: Dimensionless processing is performed on the secondary indicators, membership functions of the original indicators are established, and the comprehensive evaluation index score is calculated using a weighted average and step-by-step convergence method.

[0172] S83: Based on the comprehensive evaluation index score and the compliance status of the limiting indicators, determine the clean production level of the slag powder manufacturing enterprise, and prepare a clean production evaluation report, which elaborates on the evaluation process, results and recommendations.

[0173] The method for determining the clean production level is as follows:

[0174] Level I represents the advanced / benchmark level of clean production: all restrictive indicators meet the Level I benchmark requirements, the comprehensive evaluation index score YⅠ≥85 points, and all non-restrictive indicators meet the Level II benchmark requirements;

[0175] Level II represents the clean production access level: all restrictive indicators meet the Level II benchmark requirements, the comprehensive evaluation index score YⅡ≥85 points, and all non-restrictive indicators meet the Level III benchmark requirements.

[0176] Level III represents the general level of clean production: all limiting indicators meet the Level III benchmark requirements, and the comprehensive evaluation index score YⅢ=100 points;

[0177] Clean production requirements not met: The Level III limiting indicators are not met or the comprehensive evaluation index score YⅢ is less than 100.

[0178] A specific example of using this invention to quantitatively evaluate the clean production level of slag powder enterprises:

[0179] Specifically, the actual values ​​are first calculated according to the calculation formulas for each secondary indicator. For example, the unit product process power consumption is calculated using the formula... calculate;

[0180] Secondly, the membership function method is used to perform dimensionless processing on the actual values ​​of the indicators to obtain the scores of each indicator;

[0181] Then, the indicator score is multiplied by the corresponding comprehensive weight to obtain the weighted score, and the sum is used to obtain the comprehensive evaluation index.

[0182] Finally, the clean production level is assessed based on the compliance with the limiting indicators:

[0183] Level I (Advanced Level): YⅠ≥85 points, all restrictive indicators meet the Level I benchmark value, and non-restrictive indicators meet the Level II benchmark value;

[0184] Level II (Access Level): YⅡ≥85 points, restrictive indicators meet Level II benchmark values, and non-restrictive indicators meet Level III benchmark values;

[0185] Level III (General Level): YⅢ=100 points, the limiting indicators meet the Level III benchmark value;

[0186] If the limiting indicators do not meet the Level III benchmark value or the comprehensive evaluation index does not meet the corresponding requirements, it indicates that the enterprise has not met the basic requirements for clean production.

[0187] Quantitative evaluation can identify a company's strengths and weaknesses in clean production. For example, a high score in the iron recovery rate indicates good resource utilization, while a low score in carbon emissions per unit of product suggests the need to strengthen greenhouse gas emission reduction measures.

[0188] Based on the evaluation results, a clean production grading evaluation report is generated and targeted optimization suggestions are proposed.

[0189] Specifically, the evaluation report should include basic enterprise information, data collection details, scores for each indicator, a comprehensive evaluation index and level, and multi-dimensional evaluation analysis. Based on the evaluation results, optimization suggestions should be proposed for weak areas, such as:

[0190] Enterprises with high energy consumption can use waste heat from steel plants as a drying heat source, convert single-fan systems to dual-fan systems, or replace permanent magnet motors, etc.

[0191] Enterprises with low steel slag utilization rates can adopt technologies such as steel slag modification and the addition of grinding aids;

[0192] Enterprises that exceed pollutant emission standards can improve their leachate collection facilities and optimize their dust collection systems.

[0193] Enterprises with inadequate management systems should establish and improve their environmental and energy management systems and conduct clean production audits on schedule.

[0194] Figure 2 This is a schematic diagram of the weight determination process in another embodiment of the present invention, as shown below. Figure 2 As shown, the weight determination process S7′ includes:

[0195] S71′: Benchmarking and calculating the weights of primary indicators;

[0196] S72′: Benchmarking and calculating secondary weight values

[0197] S73′: Benchmarking and calculating the third-level weight values

[0198] S74′: Calculate the overall weight.

[0199] Specifically, in S71′, experts use the 1-9 scale method to construct a judgment matrix. For example, if they believe that “production process and equipment” is significantly more important than “product characteristics”, then the corresponding position is set to 5. By calculating the maximum eigenvalue and eigenvector of the judgment matrix, a consistency check is performed to ensure that the expert’s judgment logic is consistent. The eigenvectors that pass the check are normalized to obtain the subjective weights.

[0200] In S72′, different standardization formulas are used to process data according to the type of indicator to eliminate the influence of dimensions; box plot method is used to remove extreme data to avoid interference from outliers; the proportion and information utility value of each indicator are calculated. The larger the information utility value, the higher the weight of the indicator, and the objective weight is obtained accordingly.

[0201] In S73′, subjective and objective weights are integrated through a linear weighting method. The weight coefficient α is adjusted according to industry characteristics and evaluation needs to ensure that the comprehensive weights are consistent with both expert experience and the actual data characteristics of the enterprise.

[0202] In one embodiment, after calculating the comprehensive weight change rate under different weight coefficients by adjusting the weight coefficients, the method further includes:

[0203] If the rate of change of the overall weights exceeds a preset threshold (e.g., 5%), the rationality of the expert judgment matrix or the reliability of the data needs to be re-examined, and the weights recalculated after adjustment. If the rate of change is less than or equal to the threshold, the overall weights are stable and can be used for subsequent evaluation. This step effectively improves the stability and reliability of the weights, avoiding distortion of evaluation results due to weight fluctuations.

[0204] In one embodiment, after collecting the full-process production data of the slag powder enterprise, the method further includes:

[0205] The visualization platform transforms data into two-dimensional thematic maps (such as energy consumption distribution maps and pollutant emission spatial distribution maps) and three-dimensional models (such as three-dimensional layout models of production plants), enabling two-dimensional and three-dimensional linkage analysis. For example, clicking on a high-energy-consumption area in the two-dimensional map will highlight the corresponding production equipment in the three-dimensional model, intuitively showing the problem and providing visualization support for evaluation and optimization.

[0206] The clean production evaluation method for the slag powder manufacturing industry based on AHP provided by this invention overcomes the shortcomings of existing evaluation methods, such as strong subjectivity and insufficient data support, through a multi-dimensional index system and scientific weight determination method. It achieves a systematic and accurate assessment of the clean production level of slag powder enterprises, providing technical support for the green upgrading of the industry. In summary, this invention has the following beneficial technical effects:

[0207] By constructing a system of nine primary indicators and 29 secondary indicators covering the entire production process, including 10 limiting indicators, the system comprehensively covers the core aspects of slag powder production, thus solving the problem of the one-sidedness of existing evaluation indicators.

[0208] The weights are determined by coupling the AHP method and the Delphi method, which takes into account both expert experience and makes full use of the objective laws of data. The balance between subjective and objective factors is achieved by adjusting the weight coefficients, thereby improving the scientific nature of the weight determination.

[0209] Establish a standardized and quantitative evaluation process, combining a proprietary accounting formula and a tiered evaluation standard to achieve horizontal comparisons between different enterprises and vertical monitoring of the enterprises themselves, resulting in accurate and reliable evaluation results;

[0210] It generates targeted optimization suggestions, such as adopting a dual-fan system to reduce energy consumption and replacing permanent magnet motors to improve energy efficiency, providing clear guidance for enterprises to carry out clean production transformation and helping the industry achieve the green development goals of energy conservation, emission reduction and efficiency improvement.

[0211] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of one embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing the present invention.

[0212] Those skilled in the art will understand that the modules in the apparatus of the embodiments can be distributed in the apparatus of the embodiments as described in the embodiments, or they can be located in one or more devices different from this embodiment with corresponding changes. The modules of the above embodiments can be combined into one module, or they can be further divided into multiple sub-modules.

[0213] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating clean production in the slag powder manufacturing industry based on AHP, characterized in that, include: S1: Develop an evaluation plan, clarifying the evaluation purpose, scope, and content; S2: Collect technical information and data from slag powder enterprises, and collect and organize the data; S3: Based on the characteristics of the slag powder manufacturing industry, determine the specific content and calculation method of the evaluation index system, and construct an evaluation index system covering nine dimensions: production process and equipment, energy consumption, water consumption, raw / auxiliary material consumption, comprehensive resource utilization, pollutant generation and emission, greenhouse gas emission, product characteristics, and cleaner production management. S4: Determine the evaluation data collection cycle and sample size. Based on the above information, determine the evaluation data collection cycle and sample size to ensure that the data collection can fully reflect the company's clean production level. S5: Determine the location and number of data collection points and the data collection frequency based on the slag powder production process, technical characteristics, and existing data to meet the requirements for data collection of different indicators within the evaluation period. S6: Collect and test the following data in accordance with relevant standards and specifications: production process parameters, energy consumption, water consumption, raw and auxiliary material consumption, comprehensive utilization of resources, pollutant generation and emission, greenhouse gas emission, and product quality; S7: Establish a hierarchical structure, decompose the evaluation indicators into target layer, criterion layer and indicator layer from top to bottom, select appropriate scale to construct judgment matrix, and use the analytic hierarchy process combined with expert consultation to determine the weight of each level of indicator; S8: Based on the evaluation index system and weight calculation results, conduct a comprehensive evaluation of the clean production level of slag powder manufacturing enterprises and determine the clean production level of the enterprises.

2. The clean production evaluation method for the slag powder manufacturing industry based on AHP as described in claim 1, characterized in that, Step S2, in collecting and organizing data, includes the following steps: S21: Collect all relevant information about slag powder enterprises, including basic enterprise information, production process flow, equipment list, energy consumption data, raw and auxiliary material consumption data, product output and quality data, environmental protection facility operation status, environmental monitoring data, and clean production management system, to ensure the data foundation for the evaluation work; S22: Systematically organize and analyze the collected data, extract key information, and verify the authenticity and reliability of the data; S23: Based on the evaluation requirements, compile a list of technical data to be collected, specifying the types, quantities, and sources of the required data, and ensuring the completeness and systematic nature of the data collection.

3. The clean production evaluation method for the slag powder manufacturing industry based on AHP according to claim 1, characterized in that, Step S3, in constructing the evaluation index system, includes the following steps: S31: Conduct in-depth research on the characteristics of the slag powder manufacturing industry, including production process flow, main equipment types, energy consumption structure, raw and auxiliary material characteristics, and product application fields, to provide a basis for the construction of the evaluation index system; S32: Based on industry characteristics, construct an evaluation indicator system framework covering nine dimensions: production process and equipment, energy consumption, water consumption, raw / auxiliary material consumption, comprehensive resource utilization, pollutant generation and emission, greenhouse gas emission, product characteristics, and cleaner production management, and clarify the specific content and hierarchical structure of evaluation indicators at each level. The production process and equipment indicators include: raw material storage and transportation methods, single mill scale, mill type, product storage and transportation methods, steel slag ratio in raw materials, heat source for drying, energy-saving motor load, metering equipment status, and the percentage of noise reduction measures adopted for major noise sources. The energy consumption indicators include: electricity consumption per unit product process, fuel consumption per unit product, and comprehensive energy consumption per unit product. The water resource consumption indicators include: fresh water consumption per unit product and comprehensive utilization rate of industrial wastewater. The raw / auxiliary material consumption indicators include: raw material moisture content, raw material sulfur content, and raw material iron content entering the mill. The comprehensive resource utilization indicators include: iron recovery rate; The pollutant generation and emission indicators include: particulate matter emission per unit product and the installation of leachate collection facilities. The greenhouse gas emission indicators include: carbon emissions per unit product; The product characteristic indicators include: product quality; The clean production management indicators include: compliance with environmental laws and regulations, industrial policy compliance, environmental management agencies and personnel, pollutant emission monitoring, establishment and improvement of environmental management system and energy management system, clean production audit, transportation methods and transportation supervision; S33: Develop specific calculation methods for evaluation indicators at all levels, including calculation formulas for quantitative indicators and evaluation standards for qualitative indicators, to ensure the accuracy and repeatability of evaluation results; S34: Based on industrial policies and cleaner production requirements, determine limiting indicators, including raw material storage and transportation methods, product storage and transportation methods, unit product process power consumption, unit product fuel consumption, unit product comprehensive energy consumption, industrial wastewater comprehensive utilization rate, unit product particulate matter emissions, environmental protection laws and regulations compliance, industrial policy compliance, and cleaner production audit.

4. The clean production evaluation method for the slag powder manufacturing industry based on AHP according to claim 1, characterized in that, Step S4, when determining the evaluation data collection period and sample size, includes the following steps: S41: Collect detailed information on the production process of slag powder, equipment operating parameters, raw and auxiliary material characteristics, product specifications, energy consumption structure, and pollutant emission characteristics to provide a basis for determining the data collection cycle and sample size; S42: Based on the evaluation objectives and indicators, analyze the specific requirements for data collection cycle and sample size to ensure that data collection can fully reflect the company's clean production level. The assessment cycle is based on a production year and is synchronized with the production year. S43: Based on the analysis results and in accordance with relevant standards and specifications, determine the specific data collection cycle and sample size to ensure the scientific rigor and rationality of the data collection work.

5. The clean production evaluation method for the slag powder manufacturing industry based on AHP according to claim 1, characterized in that, Step S5, in determining the data acquisition points and data acquisition frequency, includes the following steps: S51: Conduct in-depth research on the production process and technical characteristics of slag powder, and clarify the requirements for setting up data collection points and the specific needs for data collection frequency; S52: Based on the analysis results, combined with the actual situation of the enterprise and the evaluation criteria, determine the specific locations and number of data collection points to ensure the comprehensiveness and representativeness of the data collection work; S53: Based on the evaluation cycle and data collection requirements, formulate a specific data collection frequency plan, clarify the data collection time and number of collections for different indicators, and ensure the accuracy and reliability of the data.

6. The clean production evaluation method for the slag powder manufacturing industry based on AHP according to claim 1, characterized in that, When collecting and testing data in step S6, the following is included: S61: Prepare the appropriate data collection tools and equipment according to the data collection requirements to ensure the smooth progress of the data collection work; S62: In accordance with relevant standards and specifications, conduct on-site data collection or testing on production process parameters, energy consumption, water consumption, raw and auxiliary material consumption, comprehensive resource utilization, pollutant generation and emission, greenhouse gas emission, and product quality to ensure the accuracy and representativeness of the data; S63: Properly process and store the collected data to avoid data loss and errors during processing and storage, and ensure the integrity and accuracy of the data.

7. The clean production evaluation method for the slag powder manufacturing industry based on AHP according to claim 1, characterized in that, When testing the data in step S6, the following is included: S61′: Comprehensively collect existing national or industry standard methods, and understand the applicable scope and specific operating procedures of various testing methods; S62′: Based on the evaluation objectives and evaluation indicators, analyze the specific requirements of the testing methods and select appropriate testing methods; S63′: Verify the selected test method to ensure its accuracy and reliability. If there is no existing standard method, the testing organization shall develop its own test method and conduct necessary methodological verification.

8. The clean production evaluation method for the slag powder manufacturing industry based on AHP according to claim 1, characterized in that, When using the analytic hierarchy process (AHP) to calculate weights, the following steps are included: S71: Decompose the evaluation indicators from top to bottom into the target layer, criterion layer and indicator layer to construct a hierarchical structure model; The target layer is the comprehensive evaluation index for clean production in the slag powder manufacturing industry. The criteria layer consists of nine primary indicators: production process and equipment, energy consumption, water consumption, raw / auxiliary material consumption, comprehensive resource utilization, pollutant generation and emission, greenhouse gas emission, product characteristics, and cleaner production management. The indicator layer consists of the secondary indicators under each primary indicator; S72: Select an appropriate scale, use the 1-9 scale method, and construct the judgment matrix for each level according to the actual situation; S73: Use Matlab to solve for the eigenvectors and eigenvalues ​​of the judgment matrix, and calculate the weights of each evaluation index; The weights of the primary indicators were determined using a combination of the analytic hierarchy process (AHP) and expert consultation. Specifically: Weighting of production process and equipment indicators: 0.24 Energy consumption indicator weight: 0.12 Water resource consumption index weight: 0.06 Weight of raw / auxiliary material resource consumption index: 0.07 Weight of resource comprehensive utilization index: 0.08 Pollutant generation and emission index weight: 0.13 Greenhouse gas emission indicator weight: 0.10 Product feature index weight: 0.06 Clean production management indicator weight: 0.14 S74: Calculate the consistency index CR of the judgment matrix according to the consistency test formula to ensure that the consistency of the judgment matrix meets the requirements. When CR > 0.1, the judgment matrix needs to be corrected until the result meets the consistency test requirements. S75: Compile the weight calculation results of each evaluation indicator into a table to provide a basis for subsequent comprehensive evaluation.

9. The clean production evaluation method for the slag powder manufacturing industry based on AHP according to claim 1, characterized in that, Step S7 uses the analytic hierarchy process (AHP) combined with expert consultation to determine the weights of each level of indicators, including: Using the analytic hierarchy process (AHP), more than 10 environmental experts, industry experts, and cleaner production experts were invited to compare the relative importance of each evaluation indicator pairwise. A judgment matrix was constructed using the 1-9 scale method. The consistency of the matrix was tested by the consistency ratio (CR). When the CR was less than 0.1, the eigenvectors were normalized, and the subjective weights of each evaluation indicator were calculated. The production data is standardized, extreme data is removed, the information entropy of each evaluation indicator is calculated, and the objective weight is calculated based on the information entropy. Determine the weighting coefficients The comprehensive weight of each evaluation index is calculated using a linear weighting method. The calculation formula is as follows: ； in, The comprehensive weight of the j-th evaluation indicator is... Let j be the subjective weight of the j-th evaluation indicator. Let be the objective weight of the j-th evaluation indicator.

10. The clean production evaluation method for the slag powder manufacturing industry based on AHP according to claim 1, characterized in that, Step S8, when conducting a comprehensive evaluation of the clean production level of slag powder manufacturing enterprises, includes: S81: Based on the evaluation index system and weight calculation results, collect specific data for each evaluation index, including production process and equipment index, energy consumption index, water resource consumption index, raw / auxiliary material resource consumption index, comprehensive resource utilization index, pollutant generation and emission index, greenhouse gas emission index, product characteristic index, and cleaner production management index. S82: Dimensionless processing is performed on the secondary indicators, membership functions of the original indicators are established, and the comprehensive evaluation index score is calculated using a weighted average and step-by-step convergence method. S83: Based on the comprehensive evaluation index score and the compliance status of the limiting indicators, determine the clean production level of the slag powder manufacturing enterprise, and prepare a clean production evaluation report, which elaborates on the evaluation process, results and recommendations. The method for determining the clean production level is as follows: Level I represents the advanced / benchmark level of clean production: all restrictive indicators meet the Level I benchmark requirements, the comprehensive evaluation index score YⅠ≥85 points, and all non-restrictive indicators meet the Level II benchmark requirements; Level II represents the clean production access level: all restrictive indicators meet the Level II benchmark requirements, the comprehensive evaluation index score YⅡ≥85 points, and all non-restrictive indicators meet the Level III benchmark requirements. Level III represents the general level of clean production: all limiting indicators meet the Level III benchmark requirements, and the comprehensive evaluation index score YⅢ=100 points; Clean production requirements not met: The Level III limiting indicators are not met or the comprehensive evaluation index score YⅢ is less than 100.

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