CN110472341B - Green comprehensive evaluation method for manufacturing process of marine diesel engine parts - Google Patents
Green comprehensive evaluation method for manufacturing process of marine diesel engine parts Download PDFInfo
- Publication number
- CN110472341B CN110472341B CN201910760408.1A CN201910760408A CN110472341B CN 110472341 B CN110472341 B CN 110472341B CN 201910760408 A CN201910760408 A CN 201910760408A CN 110472341 B CN110472341 B CN 110472341B
- Authority
- CN
- China
- Prior art keywords
- evaluation
- green
- index
- weight
- manufacturing process
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Abstract
The invention discloses a green comprehensive evaluation method for a marine diesel engine part manufacturing process, which automatically performs index weight normalization processing according to weight information of a plurality of evaluation indexes selected by a user to obtain evaluation index weights; and calculating by adopting different evaluation algorithms to obtain various to-be-processed green evaluation results of the target part, further determining the weight of the to-be-processed green evaluation results, and generating a green comprehensive evaluation result. The invention aims at the difficulties and limitations of the application of the existing multi-index evaluation method in the marine diesel engine part manufacturing industry, and solves the problems of complex and complicated flow, rigid and limited evaluation indexes, limited data, different algorithm result differences and the like in the green evaluation process of marine diesel engine part manufacturing enterprises on the basis of a green target.
Description
Technical Field
The invention relates to the field of green comprehensive evaluation of marine diesel engine part manufacturing processes, in particular to a green comprehensive evaluation method of a marine diesel engine part manufacturing process.
Background
With the popularization and application of the multi-index evaluation method, the green comprehensive evaluation of the manufacturing process of the manufacturing enterprises becomes an important means for the enterprises to implement green manufacturing.
However, the existing multi-index evaluation method has many difficulties and limitations in the green evaluation of the manufacturing process of marine diesel engine part manufacturing enterprises.
The evaluation analysis process is complicated, and the integrity of the evaluation range is required in the evaluation process, so that for all evaluation stages of the evaluation product, which relate to a plurality of unit processes or a plurality of parts, the cooperation of a plurality of departments such as design, process, management, information and the like and even a plurality of enterprises is required, the personnel utilization, the time consumption, the cost and the enterprise implementation difficulty are high.
The evaluation indexes are various, some indexes can be quantified, some indexes are fuzzy, how to carry out comprehensive configuration on different types of indexes, and the weights of different indexes are reasonably distributed, so that the final result is more accurate, a huge database needs to be established, and the labor cost and the time cost are high.
The traditional evaluation index is not flexible enough and has great limitation. The evaluation index system of the traditional multi-target evaluation method focuses on the influence of a product system on the global property, the regional property or the local property, the evaluation indexes are more suitable for the decision of a green department or a government department, and enterprises cannot visually see the information related to the benefits of the enterprises, so that the implementation enthusiasm of the enterprises is influenced.
Because the evaluation methods are selected differently, the evaluation results are different, because the emphasis points of each weighting method considering the problems are different, certain advantages and defects are provided in the weight calculation, and the corresponding application ranges are different greatly. In order to eliminate the difference caused by different methods and make the evaluation results universal, the comprehensive evaluation of the results needs to be considered.
Effective evaluation needs a large amount of data as a basis, and currently, some foreign evaluation software collects a large amount of data resources, but basically is industrial data of developed countries such as europe and the united states, and cannot represent the technical level of developing countries. Meanwhile, because the basic data such as material consumption, energy consumption, environmental attributes of emission and the like are different, the results obtained by evaluating the foreign data are difficult to meet the national conditions of China. In addition, the evaluation software is used for evaluating the existing products so as to acquire data, and a certain feedback mechanism is lacked.
At present, most evaluation methods only pay attention to the influence of the whole stage of a product system on the environment, the mutual greenness influence among stages in the production process is less considered, and the optimization analysis of the scheme has certain limitation.
Disclosure of Invention
Aiming at the difficulties and limitations of the application of the conventional multi-index evaluation method in the manufacturing industry of marine diesel engine parts in China, the invention aims to provide a multi-index green comprehensive evaluation method for machining products, which is based on a green target and solves the problems of complicated flow, various evaluation index types, index rigidity and limitations, data limitation, result difference and the like when an enterprise evaluates the manufacturing process of the marine diesel engine parts.
The invention adopts the following technical scheme:
a green comprehensive evaluation method for a marine diesel engine part manufacturing process automatically performs index weight normalization processing according to weight information of a plurality of evaluation indexes selected by a user to obtain evaluation index weights; and calculating by adopting different evaluation algorithms to obtain various to-be-processed green evaluation results of the target part, further determining the weight of the to-be-processed green evaluation results, and generating a green comprehensive evaluation result.
Preferably, the method comprises the following steps:
s1, determining a target part, if the target part has the support of an instance library, generating a green comprehensive evaluation result, otherwise, executing a step S2;
s2, determining an evaluation index of the target part based on the target part to form an evaluation index system list;
s3, obtaining evaluation factors based on the evaluation index system list, and calculating the membership degree of each evaluation index based on the evaluation factors;
s4, acquiring weight information of each evaluation index, and carrying out normalization processing on the weight information to obtain evaluation index weight;
s5, calculating by adopting various algorithms to obtain a plurality of to-be-processed green evaluation results;
s6, determining the weight of each to-be-processed green evaluation result, and generating a green comprehensive evaluation result based on all to-be-processed green evaluation results and the weight thereof;
and S7, generating a corresponding result explanation based on the green comprehensive evaluation result.
Preferably, step S1 comprises:
and determining the target part, calling the green comprehensive evaluation result information as a green comprehensive evaluation result if the evaluation case library has the green comprehensive evaluation result information corresponding to the target part, and otherwise, executing the step S2.
Preferably, step S2 comprises:
acquiring user evaluation demand information and/or evaluation index library information, determining an evaluation index corresponding to the target part based on the user evaluation demand information and/or the evaluation index library information, and forming an evaluation index system list.
Preferably, step S3 comprises:
acquiring an evaluation factor corresponding to the evaluation index system list from historical research data, or acquiring data corresponding to the evaluation index system list from a workshop to form the evaluation factor;
and carrying out data processing on each evaluation factor according to a preset algorithm, and calculating to obtain the membership degree of each evaluation index.
Preferably, step S4 comprises:
acquiring the weight information of the evaluation index from a weight accumulation evaluation example library, or acquiring the corresponding algorithm calculation weight information from a weight determination algorithm library;
and after the weight information is modified, normalizing all the weight information, and uniformly expanding or reducing the proportion to enable the sum of the weights to be 1 to obtain the evaluation index weight.
Preferably, step S5 includes:
selecting a plurality of algorithms from an evaluation algorithm library;
and respectively calculating a green evaluation result to be processed by utilizing each algorithm based on the membership degree of each evaluation index and the corresponding evaluation index weight.
Preferably, the method further comprises the following steps:
and S8, storing the green comprehensive evaluation result into an evaluation case library.
Compared with the prior art, the invention has the following beneficial effects:
(1) In the aspect of an evaluation process, the method has green evaluation requirements on the whole manufacturing process of parts of the marine diesel engine in the actual evaluation work, the continuous evaluation process can increase the reliability of data, and evaluation support can be provided for a corresponding green design tool set to meet actual and enterprise requirements.
(2) In the aspect of evaluation indexes, the evaluation system which is established by research at each stage and accords with the actual evaluation purpose of an enterprise is different in evaluation emphasis and different in selected index system for different products. Aiming at specific products, index redundancy or loss often occurs in a set of complete evaluation system, and meanwhile, most of the existing evaluation software is developed based on a fixed business process, and the evaluation system cannot be dynamically adjusted along with the change of evaluation requirements. If the user evaluation requirements can be tightly held at the initial stage of evaluation, and the configuration of the index system is realized, the problems of rigidity and solidification of the index system can be effectively solved, so that the evaluation work is more targeted, the practicability and flexibility of evaluation software are greatly enhanced, and great advantages are brought to the development of the evaluation work.
(3) In the aspect of weight algorithm, the invention avoids the problem of index redundancy or loss as much as possible by modifying (adding or deleting) weight information, then normalizes the obtained weights of different indexes, and makes the sum of the weights be 1 by uniformly expanding or reducing a certain proportion. Because any empowerment algorithm has the advantages and disadvantages and the application range, for most subjective empowerment methods, the empowerment process is strong, the requirement on scoring personnel is high, and the operability is weak; for objective weighting, the subjective intention of the decision maker is often ignored depending on the fact data too much. In order to reduce the problems of algorithm defects and poor operability, the invention carries out weight determination through weight examples in an authoritative weight accumulation evaluation example library. If no weight related factor score or user dissatisfaction with the recommendation weight exists in the evaluation example base, weight algorithm determination can be carried out.
(4) In the aspect of an evaluation method, the massive databases provided by the invention have important significance on the rationality and scientificity of evaluation results, meanwhile, the weights of different evaluation algorithms are determined according to the databases, the obtained multiple to-be-processed green evaluation results are subjected to weighting processing to obtain a final green comprehensive evaluation result, and the difference caused by different methods can be eliminated.
Drawings
For purposes of promoting a better understanding of the objects, aspects and advantages of the invention, reference will now be made in detail to the present invention as illustrated in the accompanying drawings, in which:
FIG. 1 is a flow chart of a green comprehensive evaluation method for a marine diesel engine part manufacturing process, which is disclosed by the invention;
FIG. 2 is a system diagram of green evaluation indexes in the manufacturing process of marine diesel engine parts.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
As shown in fig. 1 and fig. 2, the invention discloses a green comprehensive evaluation method for a manufacturing process of marine diesel engine parts, which is characterized in that the method automatically performs normalization processing of index weights according to weight information of a plurality of evaluation indexes selected by a user to obtain the evaluation index weights; and calculating by adopting different evaluation algorithms to obtain various to-be-processed green evaluation results of the target part, further determining the weight of the to-be-processed green evaluation results, and generating a green comprehensive evaluation result.
When the method is implemented specifically, the method comprises the following steps:
s1, determining a target part, if the target part has the support of an instance library, generating a green comprehensive evaluation result, and if not, executing the step S2;
s2, determining an evaluation index of the target part based on the target part to form an evaluation index system list;
s3, obtaining evaluation factors based on the evaluation index system list, and calculating the membership degree of each evaluation index based on the evaluation factors;
s4, acquiring weight information of each evaluation index, and carrying out normalization processing on the weight information to obtain evaluation index weight;
s5, calculating by adopting various algorithms to obtain a plurality of to-be-processed green evaluation results;
s6, determining the weight of each to-be-processed green evaluation result, and generating a green comprehensive evaluation result based on all to-be-processed green evaluation results and the weights thereof;
in the aspect of evaluation algorithms, the large number of evaluation algorithm libraries provided by the invention have important significance on the rationality and scientificity of evaluation results, the weights of different evaluation algorithms are determined according to the evaluation example library and the evaluation algorithm libraries by reasonably recognizing and grasping the advantages and disadvantages of each algorithm, and the obtained multiple green evaluation results to be processed are weighted to obtain the final green comprehensive evaluation result, so that the difference caused by the different advantages and disadvantages of each algorithm in the multi-index green comprehensive evaluation of the marine diesel engine part manufacturing process is eliminated, and the evaluation result is more accurate.
And S7, generating a corresponding result explanation based on the green comprehensive evaluation result.
And performing green comprehensive evaluation on the marine diesel engine parts, performing the evaluation result interpretation step, performing result interpretation and optimization analysis on the basis of the comprehensive evaluation result, and storing the evaluation result after permission approval in an evaluation case library.
For the evaluation scheme and the evaluation result meeting the requirement of greenness, the related data (such as membership degree or weight information) in the evaluation process can be stored in an evaluation example library after being audited by managers, and a reference basis is provided for the green comprehensive evaluation of the same type of parts.
The invention relates to a multi-index green comprehensive evaluation method, which constructs a multi-index green comprehensive evaluation system for the manufacturing process of parts of a marine diesel engine through a green comprehensive evaluation method for the manufacturing process of the parts of the marine diesel engine and a plurality of matched databases. In the invention, when green comprehensive evaluation is carried out on the manufacturing process of parts of the marine diesel engine, the multi-index means that the normalization processing of index weight is automatically carried out according to a plurality of evaluation indexes selected by a user, and the sum of the weights is 1 by uniformly expanding or reducing a certain proportion; and the comprehensive evaluation refers to weighting the evaluation results obtained by the selected different evaluation algorithms to finally obtain the comprehensive evaluation result. The comprehensive evaluation method comprises seven steps of evaluation product determination, evaluation index determination, evaluation factor input and index membership degree determination, index weight determination, evaluation algorithm selection, comprehensive evaluation and evaluation result interpretation. Compared with the prior art, the method is based on a green target, and solves the problems of complex and complicated flow, rigid and limited evaluation indexes, limited data, different algorithm result differences and the like in the green evaluation process of marine diesel engine part manufacturing enterprises.
When the green comprehensive evaluation method for the marine diesel engine part manufacturing process is used for constructing the multi-index green comprehensive evaluation system for the marine diesel engine part manufacturing process, a plurality of matched databases are needed for assistance, and the platform database comprises a product example library, an evaluation index library, a green index database and an evaluation algorithm library. And providing required data, cases, algorithms and the like in the green comprehensive evaluation process, and receiving information such as weight data and evaluation cases of which the evaluation results meet the green requirement. The following detailed description is made with respect to each supporting database:
(1) product example library
The product example library is a basic information library of parts of the marine diesel engine, and comprises information such as product materials, product parameters, product process routes, product part models and the like. The product instance library is provided and integrated by the enterprise technology department.
(2) Evaluation example library
The evaluation case base is a process that evaluation cases meeting green color requirements are continuously subjected to green comprehensive evaluation, and effective information such as index weight, membership degree and evaluation results of the evaluation process is stored in the evaluation case base after being checked by related managers, so that data reference is provided for subsequent green comprehensive evaluation, and the evaluation case base is a process which is continuously accumulated, enriched and improved.
(3) Evaluation index library
The evaluation index library is an evaluation index system established for marine diesel engine parts, and products are mainly divided into shaft sleeve parts (such as camshafts, crankshafts, bushings and cylinder sleeves), wheel disc parts (such as gears, end covers and impellers), fork frame parts (such as piston rods and fan supports) and box body parts (such as shells and cylinder bodies). Aiming at the same type of parts, the index system has stronger universality, so a set of more complete evaluation index system is established by analyzing the manufacturing process of various parts to form an evaluation index library.
(4) Green index database
The green index database is a platform green index database formed by continuously collecting and expanding green index data in the manufacturing process of an enterprise workshop, and comprises resource consumption data, energy consumption data, emission data of waste gas, waste liquid, cutting and the like, and environmental influence data of noise and the like in the manufacturing process of the enterprise.
The green evaluation index system of the marine diesel engine part manufacturing process is shown in figure 2
(5) Evaluation algorithm library
The evaluation algorithm library mainly comprises a weighting algorithm library, a membership function algorithm library, an evaluation method library and comparative quality information of each evaluation algorithm in the evaluation process, so that a user can select a reasonable and effective evaluation algorithm. Common evaluation algorithms include an expert scoring method, an analytic hierarchy process, a characteristic value method, a BP neural network method, a variation coefficient method, a standard deviation method, a TOPSIS method and a fuzzy comprehensive evaluation method.
The comparison between the common evaluation algorithm and the quality table is shown in Table 1
TABLE 1
In specific implementation, step S1 includes:
and determining a target part, calling green comprehensive evaluation result information as a green comprehensive evaluation result if the evaluation example library has the green comprehensive evaluation result information corresponding to the target part, and otherwise, executing the step S2.
The method is used for firstly determining an object to be evaluated, namely selecting the diesel engine part to be evaluated from a product case library.
Then, whether green evaluation is continued or not is determined through inquiring an evaluation example library, if an example exists, whether evaluation is continued or not is judged according to information such as an evaluation factor source, a weight evaluation quantitative source and a use algorithm in example information, and if a user is satisfied with the source and the algorithm of the example score (at the moment, the evaluation example library is considered to have green comprehensive evaluation result information corresponding to the target part), the green comprehensive evaluation result is directly added to the integrated evaluation file to obtain a green comprehensive evaluation result in the manufacturing process; and if the instance does not exist or the score of the instance is not satisfied, entering evaluation index determination.
In specific implementation, step S2 includes:
acquiring user evaluation demand information and/or evaluation index library information, determining an evaluation index corresponding to the target part based on the user evaluation demand information and/or the evaluation index library information, and forming an evaluation index system list.
The invention provides a part family concept for parts of the marine diesel engine, and divides the product into different part families by taking the structural characteristics as a dividing basis. For the same part family, the evaluation index system has strong universality, the typical products of various part families are researched and analyzed, a set of relatively complete corresponding evaluation index system is established, and the evaluation index can be determined for the products of the same part family only by selecting to add or delete the indexes under the index system. Meanwhile, an evaluation index system established by various part families is combined to form an evaluation index library of the system. Therefore, the negative influence on the evaluation result caused by different influences on resources, ecological environment, human health and the like due to the difference of function realization and structure of different types of marine diesel engine parts can be avoided.
In the invention, a user can add or delete the evaluation indexes according to the evaluation requirements to form an evaluation index system which is attached to a product and accords with practical application, so that the configuration of the indexes is realized, and a customized evaluation index system list is generated at the same time, thereby providing a basis carrier for the subsequent evaluation factor acquisition work.
In specific implementation, step S3 includes:
acquiring an evaluation factor corresponding to the evaluation index system list from historical research data, or acquiring data corresponding to the evaluation index system list from a workshop to form the evaluation factor;
and carrying out data processing on each evaluation factor according to a preset algorithm, and calculating to obtain the membership degree of each evaluation index.
The evaluation factor information is input, and can be acquired from a green index database collected in the existing research result or workshop manufacturing process, and the evaluation factor values corresponding to the parts are sequentially input according to the associated evaluation indexes. And then, carrying out data processing on the input evaluation factors according to a selection algorithm by an expert scoring method, a membership function and an evaluation example library to form a judgment matrix and determine the membership of each evaluation index.
In specific implementation, step S4 includes:
acquiring weight information of an evaluation index from a weight accumulation evaluation example library, or acquiring corresponding algorithm calculation weight information from a weight determination algorithm library;
after the weight information is modified (added or deleted), normalization processing is carried out on all the weight information, and the sum of the weights is 1 by uniformly enlarging or reducing the proportion, so that the evaluation index weight is obtained.
The index weight determination step is divided into two parts of historical recommendation weight determination and weight algorithm determination.
The weighting process involves a large amount of subjective data, which is an unavoidable drawback for the weighting algorithm. If the weighting evaluation is performed in an expert scoring mode, the steps are complicated and the workload is large. In order to reduce the problems of algorithm defects and poor operability, the weight determination is carried out by adopting a historical recommendation weight method, the core of the method is to establish a weight accumulation evaluation example library with authority, and a user can carry out weight determination by evaluating weight examples in the example library. And (4) determining a weight algorithm. If no weight related factor score exists in the evaluation example base or the user is not satisfied with the recommendation weight, weight algorithm determination can be carried out.
In specific implementation, step S5 includes:
selecting a plurality of algorithms from an evaluation algorithm library;
and respectively calculating a green evaluation result to be processed by utilizing each algorithm based on the membership degree of each evaluation index and the corresponding evaluation index weight.
In order to objectively and accurately evaluate the manufacturing process of parts of a marine diesel engine, it is necessary to establish a feasible and structurally stable evaluation method for different types of products. The establishment of the evaluation algorithm library is beneficial to customizing a proper technical method for different evaluation objects in the evaluation process, so that the scientificity and the reasonability of the evaluation result are ensured.
When a user selects an evaluation algorithm, the system provides recommendation algorithm information such as algorithm rules and algorithm examples, if the system recommendation algorithm is selected, the algorithm is directly applied, if the system recommendation algorithm is not selected, the evaluation algorithm is customized on the basis of a system evaluation algorithm library, the evaluation algorithm library mainly comprises evaluation algorithm information and comparison information of the advantages and disadvantages of the algorithms, and the user determines a proper evaluation algorithm according to the information.
As a comprehensive evaluation method, the invention supports the user to select various evaluation algorithms at the same time to obtain a plurality of green evaluation results to be processed.
When the concrete implementation, still include:
and S8, storing the green comprehensive evaluation result into an evaluation case library.
The technical effect of the method disclosed by the invention is illustrated by the following examples:
the evaluation is carried out aiming at the manufacturing process of a certain compressor impeller, and the accuracy and the superiority of the comprehensive evaluation method are proved by comparing the evaluation result of the analytic hierarchy process with the evaluation result of the comprehensive evaluation method.
Three common evaluation methods used in the examples are the Analytic Hierarchy Process (AHP), the comprehensive grey evaluation method, and the approximate ideal point method (TOPSIS method).
And evaluating the greenness of the manufacturing process of the compressor impeller based on green index data of the manufacturing process of the compressor impeller, which is acquired from a certain workshop.
A green index data acquisition table in the manufacturing process of the gas compressor impeller is formed by analyzing and tracking the list of all the working procedures in the manufacturing process of a certain gas compressor impeller. Because the collected data have different dimensions and qualitative descriptions, the underlying index factors cannot be directly compared, and thus, the collected index data need to be subjected to data processing such as non-dimensionalization and membership calculation.
For the resource attribute, the raw material consumption is a quantitative index, the greenness of the material can be measured by using the utilization rate of the material, and the higher the utilization rate is, the better the greenness degree is; in the auxiliary material consumption, the cutter consumption is a qualitative index, the consumption is evaluated by formulating a five-grade evaluation table (index data is divided into five grades, and the grades are respectively 1.0, 0.75, 0.5, 0.25 and 0), and the consumption of the cutting fluid is also evaluated by adopting the five-grade evaluation table.
For the energy attribute, the energy consumption is mainly the electric energy consumed by the operation of the machine tool, the electric energy consumption is a quantitative index, and the energy consumption value of each process is normalized to serve as the evaluation value.
As for the environmental properties, the cuttings have recyclability, so the pollution thereof is not considered; the waste gas pollution is mainly dust and irritant gas, and the collected indexes are qualitative indexes, so that the waste gas is evaluated by adopting a five-grade scoring table; the waste liquid pollution is mainly cutting fluid discharge and is also a qualitative index, and a five-grade grading table is adopted to evaluate the waste liquid pollution; the noise collection is a quantitative index obtained by measuring through a decibel meter, and according to the noise of the industrial enterprise noise health standard, the noise does not exceed 90db, and the quantitative membership function of the collected noise data is set as follows by combining the collected noise data:
for the safety attribute, the safety of operating a manual machine tool by an operator in the manufacturing process is poor, the safety of operating a totally-enclosed numerical control center is very high, and the operation safety is graded according to collected data.
And carrying out data processing such as dimensionless treatment and membership calculation on the collected green index data of the compressed air impeller to obtain a green evaluation decision matrix table in the manufacturing process of the compressed air impeller.
Table 2 green evaluation and judgment matrix table for manufacturing process of certain pressure impeller
1. Evaluation by analytic hierarchy Process
Firstly, determining index weight by an Analytic Hierarchy Process (AHP), and dividing a green evaluation index system in the manufacturing process of the compressed air impeller into two layers. Taking the weight calculation of 3 indexes (waste gas emission, waste liquid emission and noise) under the environmental attribute in an index system as an example, the relative importance among the 3 indexes is compared pairwise, and the evaluation matrixes are constructed according to a 1-9 scale method and respectively comprise the following steps:
solving the maximum characteristic value of each index weight and the judgment matrix, and calculating a consistency index CI, wherein the judgment matrix is a third-order matrix, the random consistency index RI takes a value of 0.58, and the consistency ratio CR of each judgment matrix is further calculated. The consistency ratio CR of each judgment matrix is less than 0.1, and the consistency test is met. Calculating the arithmetic mean of the weights of all indexes to obtain a weight vector of a subordinate index set of the environment attribute as
In the same way, the same layer under a certain pressure impeller manufacturing process green evaluation index system can be respectively solvedAnd finally obtaining a green index weight table in the manufacturing process of a certain compressor impeller according to the index weights of the same category, wherein the green index weight table is shown in a table 3.
TABLE 3 Green index weight of certain pressure impeller manufacturing process
And performing two-stage fuzzy comprehensive evaluation on the green quality from bottom to top according to a green evaluation matrix table obtained after the collected data are processed in the manufacturing process of the compressor impeller and a green evaluation index weight table obtained by calculation through an AHP method. Firstly, performing primary fuzzy comprehensive evaluation on the same type index set under each attribute, establishing a fuzzy evaluation matrix of each attribute according to the evaluation result to perform secondary fuzzy comprehensive evaluation, solving the membership degree of each attribute to the green evaluation of the manufacturing process, and finally obtaining the green level of a certain air compressing impeller manufacturing process through linear weighting. Calculating to obtain a secondary fuzzy comprehensive evaluation result of each procedure in the manufacturing process of a certain compressor impeller:
B＝[0.4031，0.3981，0.9280，0.4253，0.4221，0.6426，0.4332，0.5518，0.6141，0.4122，0.5590]。
therefore, it can be seen from the evaluation results that the greenness of the third step (heat treatment) is relatively high and the greenness of the second step (rough turning) is relatively poor in the entire production process of the compressor impeller.
2. Comprehensive evaluation
2.1 comprehensive evaluation of Grey color
The method is characterized in that a grey comprehensive evaluation method is used for carrying out green evaluation on a manufacturing process of a certain pressure impeller, and the following data are required to be obtained:
(1) Green evaluation judgment matrix table (Table 2) in certain pressure impeller manufacturing process
(2) Determining the optimal value of each index according to the evaluation matrix table, taking two indexes of material utilization rate and cutter consumption as examples, and obtaining the optimal values which are respectively the highest material utilization rate and the lowest cutter consumption, so as to obtain an optimal index set by the method:
V＝[1，0.25，0.5，0.0000，0.25，0.5，0，0.75]
(3) According to a green index weight set in a certain compressed air impeller manufacturing process, an index weight can be obtained according to the green index weight (table 3) in the certain compressed air impeller manufacturing process:
w＝[0.064，0.087，0.054，0.314，0.220，0.080，0.037，0.144]
carrying out dimensionless processing on data according to the gray comprehensive evaluation standard steps, calculating an evaluation coefficient, and finally calculating to obtain a gray comprehensive evaluation result of each process in the manufacturing process of a certain compressor impeller:
B＝[0.8956，0.8864，0.6731，0.9277，0.9221，0.7852，0.8988，0.9170，0.8822，0.9412，0.8954]
2.2 evaluation by approximation to ideal Point method (TOPSIS method)
In green indexes of a certain compressed air impeller manufacturing process, the lower the numerical value of six indexes of cutter consumption, cutting fluid consumption, electric energy consumption, waste gas emission, waste liquid emission and noise is, the better the numerical value is, and the three indexes are called as low-quality indexes; the higher the value of other indexes, the better, it is called high-quality index. The low-priority index can be converted into high-priority index by using relative number low-priority index x, using difference method (1-x), and absolute number low-priority index x using reciprocal method
The low-quality indexes in the example are all converted by a difference method, and the data after conversion are shown in a table 4.
TABLE 4 conversion index values
Combining a green index weight set w = [0.064,0.087,0.054,0.314,0.220,0.080,0.037,0.144] in a certain gas impeller manufacturing process, constructing a normalized decision matrix and a weighting matrix according to standard steps of an approach ideal point method, determining an ideal solution and a negative ideal solution, and finally obtaining an evaluation result of each process in the certain gas impeller manufacturing process through calculating the approach:
B＝[0.4613，0.4593，0.0775，0.4830，0.4819，0.2903，0.4835，0.3516，0.3052，0.7678，0.4316]
2.3, comprehensive evaluation results
Combining expert suggestions and the application range and advantages and disadvantages of the algorithm, endowing the three algorithms with different weights w = [0.1,0.2,0.7], and finally obtaining comprehensive evaluation results of the comprehensive three evaluation methods:
B*＝[0.5424，0.5386，0.2817，0.5662，0.5640，0.4245，0.5615，0.4847，0.4515，0.7669，0.5371]
from the overall evaluation results, it can be seen that the greenness in the tenth step (dynamic balance) is the highest and the greenness in the third step (heat treatment) is the worst in the entire production process of the compressor impeller. This is quite different from the results obtained using the analytical method alone.
Through production field investigation, the resource consumption, energy consumption and environmental pollution of heat treatment are very large, while the heat treatment obtained by an analytic hierarchy process is an optimal green process which does not accord with the actual situation, but only a small amount of dust is generated in the process by dynamic balance, the energy consumption is minimum, and the requirement of green is met.
Therefore, the application range and the advantages and the disadvantages of each evaluation method can be obtained, only a plurality of feasible evaluation methods are comprehensively used, different weights are given to different evaluation methods, the final green comprehensive evaluation result can be obtained through comprehensive consideration, and the difference caused by different methods can be eliminated.
Finally, it is noted that the above-mentioned embodiments illustrate rather than limit the invention, and that, while the invention has been described with reference to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (6)
1. A green comprehensive evaluation method for a marine diesel engine part manufacturing process is characterized in that index weight normalization processing is automatically carried out according to weight information of a plurality of evaluation indexes selected by a user to obtain evaluation index weights; calculating to obtain various to-be-processed green evaluation results of the target part by adopting different evaluation algorithms, further determining the weight of the to-be-processed green evaluation results, and generating a green comprehensive evaluation result; the method comprises the following specific steps:
s1, determining a target part, if the target part has the support of an instance library, generating a green comprehensive evaluation result, otherwise, executing a step S2;
s2, determining an evaluation index of the target part based on the target part to form an evaluation index system list;
s3, obtaining evaluation factors based on the evaluation index system list, and calculating the membership degree of each evaluation index based on the evaluation factors;
s4, acquiring weight information of each evaluation index, and carrying out normalization processing on the weight information to obtain evaluation index weight;
s5, calculating by adopting various algorithms to obtain a plurality of to-be-processed green evaluation results; the method comprises the following steps: selecting a plurality of algorithms from an evaluation algorithm library; respectively calculating a green evaluation result to be processed by utilizing each algorithm based on the membership degree of each evaluation index and the corresponding evaluation index weight;
s6, determining the weight of each to-be-processed green evaluation result, and generating a green comprehensive evaluation result based on all to-be-processed green evaluation results and the weights thereof;
and S7, generating a corresponding result explanation based on the green comprehensive evaluation result.
2. The green comprehensive evaluation method for the manufacturing process of the marine diesel engine component according to claim 1, wherein the step S1 comprises:
and determining a target part, calling green comprehensive evaluation result information as a green comprehensive evaluation result if the evaluation example library has the green comprehensive evaluation result information corresponding to the target part, and otherwise, executing the step S2.
3. The green comprehensive evaluation method for the manufacturing process of the marine diesel engine component according to claim 1, wherein the step S2 comprises:
acquiring user evaluation demand information and/or evaluation index library information, determining an evaluation index corresponding to the target part based on the user evaluation demand information and/or the evaluation index library information, and forming an evaluation index system list.
4. The green comprehensive evaluation method for the manufacturing process of the marine diesel engine component according to claim 1, wherein the step S3 comprises:
acquiring an evaluation factor corresponding to the evaluation index system list from historical research data, or acquiring data corresponding to the evaluation index system list from a workshop to form the evaluation factor;
and carrying out data processing on each evaluation factor according to a preset algorithm, and calculating to obtain the membership degree of each evaluation index.
5. The green comprehensive evaluation method for the manufacturing process of the marine diesel engine component according to claim 1, wherein the step S4 comprises:
acquiring weight information of an evaluation index from a weight accumulation evaluation example library, or acquiring corresponding algorithm calculation weight information from a weight determination algorithm library;
and after the weight information is modified, normalization processing is carried out on all weight information, and the sum of the weights is 1 by uniformly expanding or reducing the proportion, so that the evaluation index weight is obtained.
6. The green comprehensive evaluation method for the manufacturing process of the marine diesel engine component according to claim 1, further comprising:
and S8, storing the green comprehensive evaluation result into an evaluation case library.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910760408.1A CN110472341B (en) | 2019-08-16 | 2019-08-16 | Green comprehensive evaluation method for manufacturing process of marine diesel engine parts |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910760408.1A CN110472341B (en) | 2019-08-16 | 2019-08-16 | Green comprehensive evaluation method for manufacturing process of marine diesel engine parts |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110472341A CN110472341A (en) | 2019-11-19 |
| CN110472341B true CN110472341B (en) | 2022-12-23 |
Family
ID=68511878
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910760408.1A Active CN110472341B (en) | 2019-08-16 | 2019-08-16 | Green comprehensive evaluation method for manufacturing process of marine diesel engine parts |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110472341B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112580924B (en) * | 2020-11-16 | 2024-03-05 | 广东省东莞市质量监督检测中心 | Green degree model of infant paper diaper and construction method thereof |
| CN113449981A (en) * | 2021-06-25 | 2021-09-28 | 广东诚誉工程咨询监理有限公司 | Standardized comprehensive fuzzy evaluation model for power engineering quality management |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103530134A (en) * | 2013-10-30 | 2014-01-22 | 重庆大学 | Configurable software platform structure |
| CN108984830A (en) * | 2018-06-07 | 2018-12-11 | 湖北大学 | A kind of building efficiency evaluation method and device based on FUZZY NETWORK analysis |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130311216A1 (en) * | 2012-05-16 | 2013-11-21 | Sap Ag | Product sustainability evaluation |
| JP6478496B2 (en) * | 2014-07-03 | 2019-03-06 | キヤノン株式会社 | Imaging apparatus and control method thereof |
| CN107122899A (en) * | 2017-04-19 | 2017-09-01 | 青岛大学 | A kind of stone machining processing green evaluation system and diagnostic method |
-
2019
- 2019-08-16 CN CN201910760408.1A patent/CN110472341B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103530134A (en) * | 2013-10-30 | 2014-01-22 | 重庆大学 | Configurable software platform structure |
| CN108984830A (en) * | 2018-06-07 | 2018-12-11 | 湖北大学 | A kind of building efficiency evaluation method and device based on FUZZY NETWORK analysis |
Non-Patent Citations (4)
| Title |
|---|
| Green Manufacturing"s Adoption by Indonesian SMEs:A Conceptual Model;Sctyaningsih等;《网页在线公开：https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8607389》;20190113;第1-5页 * |
| 基于工艺特征局部优化的绿色工艺优化方法研究;周建彬等;《新型工业化》;20140116;第18-30页 * |
| 常用评价方法比较及林业绿色经济评价方法选择;刘智慧等;《林业经济》;20160225(第02期);全文 * |
| 船舶柴油机配套行业可配置绿色评价体系研究;姚金林;《中国优秀硕士学位论文全文数据库 经济与管理科学辑》;20190415;J150-225 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110472341A (en) | 2019-11-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110472341B (en) | Green comprehensive evaluation method for manufacturing process of marine diesel engine parts | |
| CN111695734A (en) | Multi-process planning comprehensive evaluation system and method based on digital twin and deep learning | |
| CN107146009B (en) | Water supply pipe network operation state evaluation method | |
| CN108170769A (en) | A kind of assembling manufacturing qualitative data processing method based on decision Tree algorithms | |
| Lv et al. | A multi-objective decision-making method for machining process plan and an application | |
| JP2021068435A (en) | Supplier evaluation device and supplier evaluation method | |
| Madhavi et al. | Evaluation of optimum turning process of process parameters using DOE and PCA Taguchi method | |
| CN111340306A (en) | Machine tool equipment optimization method for intelligent manufacturing | |
| Zhang et al. | Integrating sustainability assessment into manufacturing decision making | |
| Rao | Evaluation of metal stamping layouts using an analytic hierarchy process method | |
| CN111126865A (en) | Technology maturity judging method and system based on scientific and technological big data | |
| CN115063056A (en) | Construction behavior safety risk dynamic analysis method based on graph topology analysis improvement | |
| CN110390138A (en) | A kind of comprehensive preferred method of the multiple target of tool holder | |
| Amin et al. | A new DEA model for technology selection in the presence of ordinal data | |
| Comesaña-Campos et al. | The Value Index as a decision support tool applied to a new system for evaluating and selecting design alternatives | |
| CN109447453B (en) | Method for evaluating packaging greenness through multi-stage network data envelope analysis model | |
| Jansson et al. | Generalized measures of manufacturability | |
| CN115204634A (en) | Method and system for evaluating quality of agricultural crops based on grey correlation degree and game theory | |
| CN112215514A (en) | Operation analysis report generation method and system | |
| CN115705541A (en) | Full life cycle evaluation system of wind driven generator | |
| CN109034567B (en) | Method for predicting manufacturing technology evolution direction based on scientific and technological literature | |
| CN112990691A (en) | Mobile pressure vessel emergency plan evaluation method based on hesitation fuzzy set | |
| Bauswein et al. | Developing a cost comparison technique for hand layup versus automated fibre placement, and infusion versus out-of-autoclave | |
| CN110765600A (en) | Method and system for evaluating capability of calculation analysis software of aircraft engine | |
| Gu et al. | A priority index based method for identifying influential design factors in product service-oriented designs |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |