1 Introduction The environment, resources, and population are the three major issues facing human society today. Environmental deterioration caused by human activities is a serious threat to the survival and development of human society. In recent years, the International Organization for Standardization has successively issued quality management system standards (ISO9000 series), environmental management system standards (ISO14001), and occupational safety and health management system standards (OHSAS18001), integrating quality management, environmental management, and occupational safety and health management. The comprehensive management of the enterprise provides management tools and tools for the enterprise to comprehensively improve its management level and strengthen its overall strength. As environmental issues caused by the manufacturing industry are becoming increasingly acute, an advanced manufacturing model that adapts to sustainable development strategies - green manufacturing has emerged. Green manufacturing is a modern manufacturing model that comprehensively considers environmental impact and resource efficiency. The goal is to make the product's (negative) impact on the environment during the entire product life cycle from design, manufacture, packaging, transportation, use to end-of-life disposal. Zero or minimum, so that the consumption of resources as small as possible, and make the company's economic and social benefits coordinated optimization. In the cutting process, cutting fluid is one of the main sources of pollution causing environmental pollution. The use of green cutting fluids to reduce the environmental pollution of cutting fluids has become one of the research hotspots in the field of green manufacturing. The University of Michigan Technical University has studied the appropriate amount of cutting fluid in the cutting process, trying to minimize the amount of cutting fluid in the case of meeting the processing requirements in order to minimize the costs associated with the cutting fluid. The United States Thyssen Manufacturing Corporation is fully researching the "minimum lubrication" processing technology, so that the cutting fluid flow or aerosol through the tool in the processing area, cutting fluid flow control by the CNC program, the effect is ideal. Sun Jianguo of Shandong University of Technology studied the greenness of cutting fluid based on the product life cycle. Production practice shows that a reasonable choice of cutting fluid can fully exert the performance of cutting fluid, saving processing costs, and reduce the pollution of the cutting fluid to the environment. Therefore, the optimization of the cutting fluid is one of the important ways to reduce the cutting fluid contamination during processing. . In this paper, based on a comprehensive consideration of cutting fluid quality, cost, and environmental impact, a comprehensive selection model of cutting fluid and its constraint conditions for green manufacturing are established, and the application method and feasibility of the model are combined with production examples. Analysis and verification. 2 The establishment of an integrated selection model for cutting fluids for green manufacturing The author has conducted long-term research on the resources and energy issues in manufacturing systems directly related to green manufacturing since the early 1980s, and proposed the T-time based on green manufacturing. ), Q (Quality), C (Cost), E (Environmental Impact), R (Resources Consumption) and other five decision-making objective variables of the decision-making target system and the corresponding decision-making framework model. Any decision-making issue in green manufacturing is related to some (or all) of the above five decision-making target variables. The above model is only for the manufacturing system, it does not establish a specific cutting fluid comprehensive selection model. Based on the green manufacturing target system and decision model, combined with the specific problems in the selection of cutting fluid, this paper proposes a cutting fluid decision-making target system and a decision-making target decomposition frame variable set for green manufacturing, and on this basis, it has established Operational cutting fluid comprehensive selection model. Cutting fluid decision-making problem for green manufacturing Target system The comprehensive selection of cutting fluid for green manufacturing is a multi-objective, qualitative and quantitative combination of complex decision-making problems. To establish a decision model, you first need to determine the decision variables, which are the goals pursued by the decision-making activities. When choosing the cutting fluid in the traditional way, the target variables that people pursue are mainly quality (Q) and cost (C). Among them, the quality mainly refers to the lubrication, cooling and cleaning performance of the cutting fluid, its life cycle and utilization rate; the costs include the economic costs (material costs, facilities and equipment costs, labor costs, energy costs), user costs (use costs, maintenance (cost) and other miscellaneous costs. In the manufacturing industry of industrialized countries, when selecting the cutting fluid, in addition to meeting the requirements of the cutting process, more attention should be paid to the hazards of the cutting fluid to human health, waste liquid treatment, and comprehensive costs. This view is gradually being accepted by the domestic cutting and processing industry. The decision-making target system for cutting fluid selection for green manufacturing considers the environmental impact (E) as an important factor, ie, the target variables of the cutting fluid for green manufacturing are quality (Q), cost (C), and environment (E). Among the factors, the pursuit of these three target variables results in the highest quality, lowest cost, and minimal environmental impact. There are close links among the three decision goals of Q, C, and E. Together, they constitute a decision system for cutting fluids for green manufacturing. The decomposition content of the decision target vector in this system is shown in Figure 1.
X∈Rn Among them, X* is the optimal cutting fluid type. The above-mentioned cutting fluid selection model is a multi-objective planning model established under a given environmental condition (ie, system-constraint boundary, such as limited resource control and meeting processing process requirements) and a target. The model has two constraints: gu(X) is the model inequality constraint condition; hv(X) is the model's equality constraint condition. Respectively discussed as follows: Equation constraints hv (X) For X = [x1, x2, ..., xn] T, any X is equal to 0 (that is, the scheme is not adopted) or 1 (that is, the scheme is adopted), and the synthesis is The optimal scheme X*=[x1*,x2*,...,xn*]T is the optimal value of the objective function when the equality constraint condition x1*+x2*+...+xp*=1 is satisfied. That is, Optimum[Q(X), C(X), E(X)] = [Q(X*), C(X*), E(X*)]. Inequality constraints gu(X) For the objective functions Q(X), C(X), and E(X) in the model, they meet the quality, cost, and environmental goals of different programs on the basis of satisfying the cutting process requirements. Related constraints. For X=[x1,x2,...,xn]T(x1,x2,...,xn equal to 0 or 1), find X*=[x1*,x2*,...,xn*] to satisfy the inequality constraint condition (X)≤bi(u=1,2,...,k) (where bi is the quality target constraint, the cost target constraint, the environmental target constraint, and the raw material constraint), and Optimum[Q(X), C(X), E(X)] = [Q(X*), C(X*), E(X*)]. 3 Application example analysis A machine tool factory in the hobbing process originally used 32# oil as cutting oil, has a certain hazard to the health of workers and processing equipment, and waste oil is more difficult to handle. In order to implement the quality management system standards (ISO9000 series), environmental management system standards (ISO14001) and occupational safety and health management system standards (OHSAS18001), the plant hopes to adopt a domestic new-style green synthetic cutting fluid SG-3 or imported synthetic cutting fluid. (3% Synthetic Oil) to replace the traditional 32 # oil. Using the decision-making model of comprehensive selection of cutting fluid for green manufacturing proposed in this paper, a systematic decision can be made on this issue. The scheme description equation describing the problem is X=[x1,x2,x3] where: Xi(i=1,2,3)={ 0—the i th scheme 1 is not adopted—the i th scheme X {( X1=1, x2=0, x3=0) = scheme A1, that is, 32# oil (x1=0, x2=1, x3=0) = scheme A2, that is, a new type of domestic cutting fluid (x1=0, x2) =0, x3=1)=Option A3, that is, the objective function of the imported synthetic cutting fluid is used to evaluate the quality function Q(X), the cost function C(X) and the environmental impact function E according to the cutting fluid decision-making target system for green manufacturing. X) Include the decomposition content (see Figure 1) and establish a comprehensive evaluation system for the three cutting fluid solutions shown in Table 1. In the decision-making process, three objective functions are evaluated comprehensively using fuzzy clustering methods to obtain quantitative evaluation results, which reflect the final optimization results of the three schemes. The comprehensive evaluation system includes three evaluation aspects. Each evaluation aspect includes multiple evaluation elements. Each evaluation element also includes different evaluation factors. Each evaluation, evaluation factors and evaluation factors are configured with different weights. The evaluation levels can be set to the same number of levels, ie V={v1, v2, v3}, respectively denoted as: Good/Normal/Poor. The establishment of a decision model Based on the aforementioned method of establishing a decision model, a comprehensive selection model of cutting fluid for this application example can be established as follows: For X = [x1, x2, x3] (x1, x2, x3 = 0 or 1), find X* =[x1*,x2*,x3*], satisfies the constraints: x1* + x2* +x3*=1, making Optimum[Q(X),C(X),E(X)]=[Q(X *), C(X*), E(X*)]. Fuzzy Evaluation of Three Types of Cutting Fluid Solutions Based on the decision model, decision-variable evaluation element sets were established for three types of cutting fluid solutions, and fuzzy evaluation was performed. Scenario A1 (32# oil cutting oil) Sets the cutting fluid quality (Q) evaluation element set U11U11 = {u1 (lubrication performance), u2 (cooling performance), u3 (cleaning performance), u4 (use cycle)} 11 Establish cutting Liquid quality (Q) evaluation factor fuzzy matrix R11 According to professional testing methods combined with expert survey method, the fuzzy matrix is ​​expressed by membership degree, and the fuzzy evaluation matrix R11 for the evaluation quality of cutting fluid quality (Q) is R11 = [0.5 0.3 0.2 ] 0.5 0.3 0.2 0.5 0.3 0.2 0.55 0.25 0.18 11 Establishment of cutting fluid quality (Q) Evaluation factor Weight coefficient matrix A11A11 = (0.3, 0.3, 0.3, 0.1) 11 Calculated cutting fluid quality (Q) Evaluation element Comprehensive evaluation matrix B1 B1 = A11R11 = (0.3, 0.3, 0.3, 0.1) 11 [0.5 0.3 0.2 ] 0.5 0.3 0.2 0.5 0.3 0.2 0.55 0.25 0.18 11 = (0.505, 0.295, 0.198) By analogy, the environmental impact (E) element evaluation matrix of the cutting fluid can be obtained B21, B22, B23 and cutting fluid cost (C) element evaluation matrix B31, B32, B33. After the above two-layer comprehensive evaluation, the comprehensive evaluation matrix B of the cutting fluid solution A1 is shown in Table 1. Three kinds of cutting fluid solutions Comprehensive evaluation Target system Evaluation Aspects Evaluation factors Evaluation factors Evaluation level No. i ui Weight ai Number j uij Weight aij Sequence number k Uijk weight v1 v2 v3 fuzzy matrix good difference 1 quality (Q) 0.4 1 lubrication 0.3 A1 lubrication 1 0.50 0.30 0.20 A2 lubrication 1 0.70 0.25 0.05 A3 lubrication 1 0.80 0.15 0.05 2 cooling 0.3 A1 cooling 1 0.50 0.30 0.20 A2 cooling 1 0.70 0.25 0.05 A3 Cooling 1 0.80 0.15 0.05 3 Cleaning 0.3 A1 Cleaning 1 0.50 0.30 0.20 A2 Cleaning 1 0.70 0.25 0.05 A3 Cleaning 1 0.80 0.15 0.05 4 Utilization rate and life cycle 0.1 A1 Utilization ratio and life cycle 1 0.55 0.25 0.18 A2 Utilization ratio Use cycle 1 0.70 0.25 0.05 A3 Utilization ratio and use period 1 0.80 0.15 0.05 No more 2 Environment (E) 0.3 1 Toxicity hazard 0.25 A1 Toxicity hazard 1 0.5 0.3 0.20 A2 Toxicity hazard 1 0.7 0.25 0.05 A3 Toxicity hazard 1 0.75 0.20 0.05 2 Safety index 0.35 A1 Hazard to humans 0.3 0.6 0.3 0.10 A2 Hazard to humans 0.3 0.7 0.25 0.05 A3 Hazard to humans 0.3 0.80 0.20 0 A1 Equipment safety 0.25 0.50 0.3 0.20 A2 Equipment Safety 0.25 0.65 0.25 0.1 A3 Equipment Safety 0.25 0.75 0.20 0.05 A1 Corrosion/Antirust 0.25 0.55 0.3 0.15 A2 Corrosion/Antirust 0.25 0.65 0.25 0.1 A3 Corrosion/Antirust 0.25 0.70 0.2 0.1 A1 Fire safety 0.2 0.8 0.2 0 A2 Fire safety 0.2 1.0 0 0 A3 Fire safety 0.2 1.0 0 0 3 Environmental index 0.4 A1 Water and soil contamination 0.6 0.45 0.3 0.25 A2 Water and soil contamination 0.6 0.6 0.25 0.15 A3 Water body and soil pollution 0.6 0.70 0.20 0.10 A1 Waste pollution 0.4 0.40 0.3 0.3 A2 Waste pollution 0.4 0.6 0.2 0.2 A3 Waste pollution 0.4 0.70 0.20 0.10 3 Cost (C) 0.3 1 Production cost 0.5 A 1 Business cost 1 0.50 0.3 0.2 A2 Corporate cost 1 0.68 0.22 0.1 A3 Corporate cost 1 0.70 0.20 0.10 2 User cost 0.2 A1 Use cost, maintenance cost 1 0.55 0.25 0.2 A2 Use cost, maintenance cost 1 0.60 0.20 0.2 A3 Use cost, maintenance cost 1 0.70 0.20 0.10 3 Social Cost 0.3 A1 Environmental pollution treatment costs 0.3 0.3 0.3 0.4 A2 Environmental pollution treatment costs 0.3 0.6 0.3 0.1 A3 Environmental pollution treatment costs 0.3 0.70 0.20 0.10 A1 Occupational health costs 0.4 0.5 0.3 0.2 A2 Occupational health costs 0.4 0.7 0.2 0.10 A3 Occupational health costs 0.4 0.75 0.15 0.10 A1 Waste disposal costs 0.3 0.55 0.25 0.2 A2 Waste disposal costs 0.3 0.65 0.2 0.15 A3 Waste disposal costs 0.3 0.75 0.15 0.10 Optimum[Q(X),C(X),E(X)]A1=B=AR=(0.4,0.3,0.3) [0.505 0.295 0.198 ] 0.508 0.293 0.2336 0.496 0.285 0.202 =(0.5035,0.292,0.21) Finally The total score can be used to express the comprehensive evaluation results. Generally, it is desirable to set the membership degree set to u={u1,u2,...,ui,...,un,...} to calculate the specific score of the comprehensive evaluation result. According to this score, the evaluated object can be sorted and the score calculation method can be used. For the score = 100Bu = 100 (b1, b2, ..., bi, ..., bm)
{u1,u2...,,ui,...,un,...}T=100(∑ni=1biui) If the score is used to represent the comprehensive evaluation result, the score of the evaluation criteria membership set may be u=[0.90 (good) , 0.60 (general), 0.30 (difference)] Based on this, it can be calculated that the comprehensive evaluation score of the 32# oil cutting oil is 100Bu=69.35. Scheme A2 (using domestically produced new type synthetic cutting fluid) With reference to the evaluation procedure of scheme A1, evaluation models for each evaluation element are successively established and comprehensively evaluated. Finally, the overall evaluation matrix using scheme A2 is Optimum[Q(X),C(X). ), E (X)] A2 = B = AR = (0.6565, 0.219, 0.125) Based on this, it can be calculated that the comprehensive evaluation score of the domestic new synthetic cutting fluid is 100Bu = 78.01. Scheme A3 (using imported synthetic cutting fluid) According to the evaluation procedure, evaluation models for each evaluation element are established in turn and comprehensively evaluated. Finally, the overall evaluation matrix using scheme A3 is Optimum[Q(X), C(X), E( X)] A3 = B = AR = (0.757, 0.179, 0.07) From this, it can be calculated that the comprehensive evaluation score using the imported synthetic cutting fluid is 100Bu = 80.67. The final evaluation results show that the domestic new synthetic cutting fluid and imported synthetic cutting fluid scheme are better than the original 32# oil cutting oil scheme. Taking into account the comprehensive cost factors of large-scale production, the plant finally decided to adopt a new domestic synthetic cutting fluid program, and achieved more significant comprehensive benefits (economic benefits and social benefits) in production. Application practice has proved that the comprehensive selection model of cutting fluid for green manufacturing is feasible and practical. 4 Conclusions This paper establishes a cutting fluid decision-making target system for green manufacturing, including quality (Q), cost (C), and environmental impact (E), and decomposes the decision vectors in the target system. On this basis, a comprehensive selection model of cutting fluid for green manufacturing and related constraints were established, and comprehensive evaluation methods and steps were introduced through application examples. The evaluation results verify the feasibility of the model.
Figure 1 Cutting fluid decision-making target system decomposition content for green manufacturing
X∈Rn Among them, X* is the optimal cutting fluid type. The above-mentioned cutting fluid selection model is a multi-objective planning model established under a given environmental condition (ie, system-constraint boundary, such as limited resource control and meeting processing process requirements) and a target. The model has two constraints: gu(X) is the model inequality constraint condition; hv(X) is the model's equality constraint condition. Respectively discussed as follows: Equation constraints hv (X) For X = [x1, x2, ..., xn] T, any X is equal to 0 (that is, the scheme is not adopted) or 1 (that is, the scheme is adopted), and the synthesis is The optimal scheme X*=[x1*,x2*,...,xn*]T is the optimal value of the objective function when the equality constraint condition x1*+x2*+...+xp*=1 is satisfied. That is, Optimum[Q(X), C(X), E(X)] = [Q(X*), C(X*), E(X*)]. Inequality constraints gu(X) For the objective functions Q(X), C(X), and E(X) in the model, they meet the quality, cost, and environmental goals of different programs on the basis of satisfying the cutting process requirements. Related constraints. For X=[x1,x2,...,xn]T(x1,x2,...,xn equal to 0 or 1), find X*=[x1*,x2*,...,xn*] to satisfy the inequality constraint condition (X)≤bi(u=1,2,...,k) (where bi is the quality target constraint, the cost target constraint, the environmental target constraint, and the raw material constraint), and Optimum[Q(X), C(X), E(X)] = [Q(X*), C(X*), E(X*)]. 3 Application example analysis A machine tool factory in the hobbing process originally used 32# oil as cutting oil, has a certain hazard to the health of workers and processing equipment, and waste oil is more difficult to handle. In order to implement the quality management system standards (ISO9000 series), environmental management system standards (ISO14001) and occupational safety and health management system standards (OHSAS18001), the plant hopes to adopt a domestic new-style green synthetic cutting fluid SG-3 or imported synthetic cutting fluid. (3% Synthetic Oil) to replace the traditional 32 # oil. Using the decision-making model of comprehensive selection of cutting fluid for green manufacturing proposed in this paper, a systematic decision can be made on this issue. The scheme description equation describing the problem is X=[x1,x2,x3] where: Xi(i=1,2,3)={ 0—the i th scheme 1 is not adopted—the i th scheme X {( X1=1, x2=0, x3=0) = scheme A1, that is, 32# oil (x1=0, x2=1, x3=0) = scheme A2, that is, a new type of domestic cutting fluid (x1=0, x2) =0, x3=1)=Option A3, that is, the objective function of the imported synthetic cutting fluid is used to evaluate the quality function Q(X), the cost function C(X) and the environmental impact function E according to the cutting fluid decision-making target system for green manufacturing. X) Include the decomposition content (see Figure 1) and establish a comprehensive evaluation system for the three cutting fluid solutions shown in Table 1. In the decision-making process, three objective functions are evaluated comprehensively using fuzzy clustering methods to obtain quantitative evaluation results, which reflect the final optimization results of the three schemes. The comprehensive evaluation system includes three evaluation aspects. Each evaluation aspect includes multiple evaluation elements. Each evaluation element also includes different evaluation factors. Each evaluation, evaluation factors and evaluation factors are configured with different weights. The evaluation levels can be set to the same number of levels, ie V={v1, v2, v3}, respectively denoted as: Good/Normal/Poor. The establishment of a decision model Based on the aforementioned method of establishing a decision model, a comprehensive selection model of cutting fluid for this application example can be established as follows: For X = [x1, x2, x3] (x1, x2, x3 = 0 or 1), find X* =[x1*,x2*,x3*], satisfies the constraints: x1* + x2* +x3*=1, making Optimum[Q(X),C(X),E(X)]=[Q(X *), C(X*), E(X*)]. Fuzzy Evaluation of Three Types of Cutting Fluid Solutions Based on the decision model, decision-variable evaluation element sets were established for three types of cutting fluid solutions, and fuzzy evaluation was performed. Scenario A1 (32# oil cutting oil) Sets the cutting fluid quality (Q) evaluation element set U11U11 = {u1 (lubrication performance), u2 (cooling performance), u3 (cleaning performance), u4 (use cycle)} 11 Establish cutting Liquid quality (Q) evaluation factor fuzzy matrix R11 According to professional testing methods combined with expert survey method, the fuzzy matrix is ​​expressed by membership degree, and the fuzzy evaluation matrix R11 for the evaluation quality of cutting fluid quality (Q) is R11 = [0.5 0.3 0.2 ] 0.5 0.3 0.2 0.5 0.3 0.2 0.55 0.25 0.18 11 Establishment of cutting fluid quality (Q) Evaluation factor Weight coefficient matrix A11A11 = (0.3, 0.3, 0.3, 0.1) 11 Calculated cutting fluid quality (Q) Evaluation element Comprehensive evaluation matrix B1 B1 = A11R11 = (0.3, 0.3, 0.3, 0.1) 11 [0.5 0.3 0.2 ] 0.5 0.3 0.2 0.5 0.3 0.2 0.55 0.25 0.18 11 = (0.505, 0.295, 0.198) By analogy, the environmental impact (E) element evaluation matrix of the cutting fluid can be obtained B21, B22, B23 and cutting fluid cost (C) element evaluation matrix B31, B32, B33. After the above two-layer comprehensive evaluation, the comprehensive evaluation matrix B of the cutting fluid solution A1 is shown in Table 1. Three kinds of cutting fluid solutions Comprehensive evaluation Target system Evaluation Aspects Evaluation factors Evaluation factors Evaluation level No. i ui Weight ai Number j uij Weight aij Sequence number k Uijk weight v1 v2 v3 fuzzy matrix good difference 1 quality (Q) 0.4 1 lubrication 0.3 A1 lubrication 1 0.50 0.30 0.20 A2 lubrication 1 0.70 0.25 0.05 A3 lubrication 1 0.80 0.15 0.05 2 cooling 0.3 A1 cooling 1 0.50 0.30 0.20 A2 cooling 1 0.70 0.25 0.05 A3 Cooling 1 0.80 0.15 0.05 3 Cleaning 0.3 A1 Cleaning 1 0.50 0.30 0.20 A2 Cleaning 1 0.70 0.25 0.05 A3 Cleaning 1 0.80 0.15 0.05 4 Utilization rate and life cycle 0.1 A1 Utilization ratio and life cycle 1 0.55 0.25 0.18 A2 Utilization ratio Use cycle 1 0.70 0.25 0.05 A3 Utilization ratio and use period 1 0.80 0.15 0.05 No more 2 Environment (E) 0.3 1 Toxicity hazard 0.25 A1 Toxicity hazard 1 0.5 0.3 0.20 A2 Toxicity hazard 1 0.7 0.25 0.05 A3 Toxicity hazard 1 0.75 0.20 0.05 2 Safety index 0.35 A1 Hazard to humans 0.3 0.6 0.3 0.10 A2 Hazard to humans 0.3 0.7 0.25 0.05 A3 Hazard to humans 0.3 0.80 0.20 0 A1 Equipment safety 0.25 0.50 0.3 0.20 A2 Equipment Safety 0.25 0.65 0.25 0.1 A3 Equipment Safety 0.25 0.75 0.20 0.05 A1 Corrosion/Antirust 0.25 0.55 0.3 0.15 A2 Corrosion/Antirust 0.25 0.65 0.25 0.1 A3 Corrosion/Antirust 0.25 0.70 0.2 0.1 A1 Fire safety 0.2 0.8 0.2 0 A2 Fire safety 0.2 1.0 0 0 A3 Fire safety 0.2 1.0 0 0 3 Environmental index 0.4 A1 Water and soil contamination 0.6 0.45 0.3 0.25 A2 Water and soil contamination 0.6 0.6 0.25 0.15 A3 Water body and soil pollution 0.6 0.70 0.20 0.10 A1 Waste pollution 0.4 0.40 0.3 0.3 A2 Waste pollution 0.4 0.6 0.2 0.2 A3 Waste pollution 0.4 0.70 0.20 0.10 3 Cost (C) 0.3 1 Production cost 0.5 A 1 Business cost 1 0.50 0.3 0.2 A2 Corporate cost 1 0.68 0.22 0.1 A3 Corporate cost 1 0.70 0.20 0.10 2 User cost 0.2 A1 Use cost, maintenance cost 1 0.55 0.25 0.2 A2 Use cost, maintenance cost 1 0.60 0.20 0.2 A3 Use cost, maintenance cost 1 0.70 0.20 0.10 3 Social Cost 0.3 A1 Environmental pollution treatment costs 0.3 0.3 0.3 0.4 A2 Environmental pollution treatment costs 0.3 0.6 0.3 0.1 A3 Environmental pollution treatment costs 0.3 0.70 0.20 0.10 A1 Occupational health costs 0.4 0.5 0.3 0.2 A2 Occupational health costs 0.4 0.7 0.2 0.10 A3 Occupational health costs 0.4 0.75 0.15 0.10 A1 Waste disposal costs 0.3 0.55 0.25 0.2 A2 Waste disposal costs 0.3 0.65 0.2 0.15 A3 Waste disposal costs 0.3 0.75 0.15 0.10 Optimum[Q(X),C(X),E(X)]A1=B=AR=(0.4,0.3,0.3) [0.505 0.295 0.198 ] 0.508 0.293 0.2336 0.496 0.285 0.202 =(0.5035,0.292,0.21) Finally The total score can be used to express the comprehensive evaluation results. Generally, it is desirable to set the membership degree set to u={u1,u2,...,ui,...,un,...} to calculate the specific score of the comprehensive evaluation result. According to this score, the evaluated object can be sorted and the score calculation method can be used. For the score = 100Bu = 100 (b1, b2, ..., bi, ..., bm)
{u1,u2...,,ui,...,un,...}T=100(∑ni=1biui) If the score is used to represent the comprehensive evaluation result, the score of the evaluation criteria membership set may be u=[0.90 (good) , 0.60 (general), 0.30 (difference)] Based on this, it can be calculated that the comprehensive evaluation score of the 32# oil cutting oil is 100Bu=69.35. Scheme A2 (using domestically produced new type synthetic cutting fluid) With reference to the evaluation procedure of scheme A1, evaluation models for each evaluation element are successively established and comprehensively evaluated. Finally, the overall evaluation matrix using scheme A2 is Optimum[Q(X),C(X). ), E (X)] A2 = B = AR = (0.6565, 0.219, 0.125) Based on this, it can be calculated that the comprehensive evaluation score of the domestic new synthetic cutting fluid is 100Bu = 78.01. Scheme A3 (using imported synthetic cutting fluid) According to the evaluation procedure, evaluation models for each evaluation element are established in turn and comprehensively evaluated. Finally, the overall evaluation matrix using scheme A3 is Optimum[Q(X), C(X), E( X)] A3 = B = AR = (0.757, 0.179, 0.07) From this, it can be calculated that the comprehensive evaluation score using the imported synthetic cutting fluid is 100Bu = 80.67. The final evaluation results show that the domestic new synthetic cutting fluid and imported synthetic cutting fluid scheme are better than the original 32# oil cutting oil scheme. Taking into account the comprehensive cost factors of large-scale production, the plant finally decided to adopt a new domestic synthetic cutting fluid program, and achieved more significant comprehensive benefits (economic benefits and social benefits) in production. Application practice has proved that the comprehensive selection model of cutting fluid for green manufacturing is feasible and practical. 4 Conclusions This paper establishes a cutting fluid decision-making target system for green manufacturing, including quality (Q), cost (C), and environmental impact (E), and decomposes the decision vectors in the target system. On this basis, a comprehensive selection model of cutting fluid for green manufacturing and related constraints were established, and comprehensive evaluation methods and steps were introduced through application examples. The evaluation results verify the feasibility of the model.