CN109063976A - Intelligence manufacture capability maturity evaluation method based on Fuzzy AHP - Google Patents
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Abstract
The present invention discloses a kind of intelligence manufacture capability maturity evaluation method based on Fuzzy AHP, steps are as follows: S1, establishing assessment indicator system: according to evaluation purpose, by the mode of investigation and expert consulting, the intelligence manufacture capability maturity assessment indicator system being layered step by step is established；S2, it determines weight: using analytic hierarchy process (AHP), introducing the review comment of domain expert, determine the weight of its same each index of level；S3, quantizating index: the overall development in conjunction with current intelligence manufacture maturity is horizontal, and the development level of index is uniformly used a kind of dimension；S4, fuzzy overall evaluation: according to a reference value of Comment gathers and corresponding evaluation approach collection, the degree of membership of evaluate collection fuzzy subset is obtained, constructs fuzzy relation matrix；According to the weight vectors and fuzzy relation matrix of index, the total score of maturity is obtained using weighted mean method, and then judge maturity levels locating for evaluation object.
Description
Technical field
The present invention relates to a kind of maturity to assess information processing method, more particularly, to a kind of intelligence of Fuzzy AHP
It can manufacturing capacity maturity assessment method.
Background technique
Intelligence manufacture can promote the transition and upgrade of economic growth and industry, and countries in the world are all sent out on intelligence manufacture
Power is actively laid out modern manufacturing industry.State Council promulgates that " made in China 2025 " is clearly proposed intelligence manufacture as master
Offense is to, the plan of moral state-owned industry 4.0, the new industrial revolution of American industry internet, Japanese industry value chain and France.Intelligence system
The evaluation for making capability maturity can agglomerate the common recognition of industry, avoid direction from wandering off, reduce the risk of fusion development, therefore be directed to
The research work of intelligence manufacture capability maturity evaluation focuses mostly in the standardization body of every country.German machine and system
Make Business Association issued for evaluate industry 4.0 carry out degree Capability Maturity Models, the Capability Maturity Model include strategy with tissue,
6 intelligent plant, intelligent operation, intellectual product, data-driven service and employee level-one evaluation indexes, and include that 18 second levels are commented
Valence index.The intelligence manufacture capability maturity evaluation in China is according to " national intelligence manufacture Standard System Construction guide (2015
Version) " propose system architecture, respectively from intelligent peacekeeping manufacture dimension intelligence manufacture ability is evaluated.
Existing is qualitative evaluation method to intelligence manufacture capability maturity evaluation method, and qualitative evaluating method is in reality
More subjective factor is inevitably had in operating process, therefore the evaluation of intelligence manufacture maturity is used quantitative or fixed
Property with the mode quantitatively combined will more objective, accurate reflection intelligence manufacture maturity genuine property, satisfaction works as
The era development trend of preceding digitlization, digitization.The present invention will be by " national intelligence manufacture Standard System Construction guide (2015
Version) " propose architectural framework, intelligence manufacture capability maturity assessment indicator system is established, by analytic hierarchy process (AHP) and fuzzy synthesis
Evaluation assessment combines, and assesses intelligence manufacture capability maturity, and this method can accurately reflect the intelligence of current enterprise
Manufacturing capacity.
Summary of the invention
The present invention provides a kind of intelligence manufacture capability maturity evaluation method of quantification, this method is based on fuzzy hierarchy
It is analysis integrated that maturity is evaluated, it can be improved the accuracy of maturity assessment, comprising:
Establish assessment indicator system: according to evaluation purpose, by the mode of investigation and expert consulting, foundation divides step by step
The intelligence manufacture capability maturity assessment indicator system of layer；
It determines weight: the knowledge experience of domain expert being introduced into the process that weight determines using the form of questionnaire marking
In, using mathematical method --- analytic hierarchy process (AHP) determines the weight of each index of same level；
Quantizating index: the overall development in conjunction with current enterprise intelligent manufacture maturity is horizontal, by the development level of index into
Row quantization is with unified dimension；
Fuzzy overall evaluation: according to a reference value of Comment gathers and corresponding evaluation approach collection, obtain evaluate collection fuzzy subset's
Degree of membership constructs fuzzy relation matrix；According to the weight vectors and fuzzy relation matrix of index, obtained into using weighted mean method
The total score of ripe degree, and then judge maturity levels locating for evaluation object.
Further, assessment indicator system is established, comprising:
According to evaluation purpose, establish by the mode of investigation and expert consulting by top, middle layer and most bottom
3 layers of intelligence manufacture capability maturity assessment indicator system of layer composition.
Meaning representated by each layer is defined, top is the final goal for needing to obtain, i.e. intelligence manufacture capability maturity；
Middle layer is top and the bottom relationship tie；The bottom is specifically to implement means and method in manufacturing process.
Wherein middle layer includes first class index and two-level index, and first class index covers intelligent peacekeeping manufacture dimension, two-level index
Cover design, production, logistics, sale, service, element of resource, interconnect, the system integration, information fusion and emerging industry situation；Most
Bottom includes three-level index, covers product design, industrial design, process optimization, buying, planning and scheduling, production operation, quality
It controls, 27 indexs of storage and dispatching, safe and environmental protection, logistics management, sales management, customer service, service of goods etc..
Further, it is determined that the weight of evaluation index, including
Judgement Matricies: the element of judgment matrix obtains the evaluation of estimate of two indexes relative importance using 1-9 scaling law,
For evaluation of estimate by inviting intelligence manufacture domain expert to give a mark, scoring process is mutually indepedent；
It calculates feature vector: the every row element of judgment matrix H being carried out even multiplied to Mi, then calculate MiN times root
Acquire weight
Consistency check: according to HW=λmaxW finds out the maximum eigenvalue λ of matrix Hmax, and then find out coincident indicator CI.
Random index by searching for n rank matrix obtains RI, finally obtains consistency ratio CR=CI/RI.If CR > 0.1, illustrates in H
Each Small object consistency is poor, needs to reconfigure judgment matrix, if CR≤0.1, illustrates that each Small object consistency is good in H, W is
For required each target weight.
Further, the quantization score of evaluation index, including
The score equivalent of evaluation index is at hundred-mark system, and conversion process is sufficiently according to the standard reference set both at home and abroad
Value generally acknowledges value or current value outstanding both at home and abroad both at home and abroad, and by industry field expertise.
Further, to the fuzzy overall evaluation of intelligence manufacture capability maturity, including
Formulate evaluation approach domain: (planning grade, integrates grade, is excellent specification grade five grades of intelligence manufacture capability maturity point
Change grade, lead grade), the grade label in Comment gathers directly is set by five grades, determines fuzzy son using abstract classification
Collect the grade in Comment gathers, corresponding each grade has corresponding quantization marking, and a reference value is set as V={ v1,v2,v3,v4,
v5}={ 20,40,60,80,100 }；
Building fuzzy relation matrix: the score for evaluating data is made the difference with evaluate collection, and each index is calculated with evaluation
Distance between collection takes the inverse of distance to be standardized operation, obtains the degree of membership that corresponding index is concentrated in different evaluation, obtains
Fuzzy relation matrix；
It calculates fuzzy overall evaluation result vector: carrying out weight vector and fuzzy relation matrix with the algorithm of fuzzy mathematics
The Result of Fuzzy Comprehensive Evaluation vector for being accordingly evaluated object is calculated in synthesis；
Corresponding index score is calculated according to fuzzy overall evaluation result；
By evaluate collection and the fuzzy membership of corresponding index, the corresponding score of two-level index is obtained；
Evaluation object is classified according to first class index score: in evaluation object classification process, being weighed according to first class index
Weight and first class index Calculation Estimation subject evaluation total score, and according to evaluate collection grade scale, judge which kind of rank it reaches.
The intelligence manufacture capability maturity evaluation method based on Fuzzy AHP provided through the invention, according to intelligence
Energy manufacturer's standard System Construction guide proposes the assessment indicator system being layered step by step, has been determined that evaluation refers to chromatographic assays
Target weight, finally acquires intelligence manufacture capability maturity score using the method for fuzzy synthesis, has carried out grade according to score
It divides.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is the present invention
Some embodiments for those of ordinary skill in the art without creative efforts, can also basis
These attached drawings obtain other attached drawings.
Fig. 1 is the flow diagram of the maturity assessment embodiment of the method the present invention is based on Fuzzy AHP.
Specific embodiment
In order to illustrate more clearly of the present invention, the present invention is done further below with reference to preferred embodiments and drawings
It is bright.Similar component is indicated in attached drawing with identical appended drawing reference.It will be appreciated by those skilled in the art that institute is specific below
The content of description is illustrative and be not restrictive, and should not be limited the scope of the invention with this.
Referring to Fig.1, Fig. 1 is that the present invention is based on the signals of the process of the maturity ranking method embodiment of Fuzzy AHP
Figure.
The invention proposes the maturity ranking methods based on Fuzzy AHP, include the following steps:
Step S1, by the mode of investigation and expert consulting, establishes the intelligence system being layered step by step according to evaluation purpose
Make capability maturity assessment indicator system；
In the present embodiment, according to evaluation purpose, by investigation and expert consulting mode establish by it is top,
3 layers of intelligence manufacture capability maturity assessment indicator system of middle layer and bottom composition.It is top be need obtain it is final
Target, i.e. intelligence manufacture capability maturity grade；Middle layer is top and the bottom relationship tie, one in corresponding table 1
Grade index and two-level index；The bottom is specifically to implement means and method in manufacturing process, the three-level index in corresponding table 1.
1 intelligence manufacture capability maturity evaluation index of table
Tab 1Evaluation index of intelligence manufacturing capability
maturity
Step S2, determines index weights, in the present embodiment process, by introducing the knowledge of domain expert, to index
Importance is scored to obtain judgment matrix, finally obtains the weight of index using analytic hierarchy process (AHP) according to judgment matrix, specifically
Step includes:
S2.1, Judgement Matricies H
The evaluation of estimate h for the two indexes relative importance that the element of judgment matrix H is obtained using 1-9 scaling lawi,j, it is shown in Table 2.
The form of judgment matrix H is
hi,jIndicate the evaluation of estimate of two indexes relative importance, evaluation of estimate is by inviting intelligence manufacture domain expert to beat
Point, scoring process is mutually indepedent.It has an advantage that the Heuristics of expert is utilized in evaluation procedure, reduces the master of expert estimation
The property seen, so that the weighted score of evaluation index more objective reality.11 judgment matrixs will be finally obtained according to 1-9 scaling law,
It include: U1With U2Comparison, B11,B12,B13,B14,B15Between comparison, B21,B22,B23,B24,B25Between comparison, X111,
X112,X113Between comparison, X121,X122,X123,X124,X125,X126Between comparison, X151With X152Comparison, X211,X212,
X213,X214Between comparison, X221With X222Comparison, X231With X232Comparison, X241,X242,X243Between comparison and X251,
X252,X253Between comparison.
2 importance quantizating index table of table
Tab2 Indicator table of index importance
S2.2, characteristic vector W is calculated
The every row element of judgment matrix H is carried out even multiplied to Mi, then calculate MiN times rootFinally acquire weight
ωi, calculation formula is given below:
Required characteristic vector W=[ω1,ω2,L,ωn]T。
S2.3, consistency check
According to HW=λmaxW finds out the maximum eigenvalue λ of judgment matrix Hmax, coincident indicator CI is then found out, wherein
The random index RI that n rank matrix is obtained by way of tabling look-up, is shown in Table 3,
The random index RI of table 3:n rank matrix
Tab 3The random index RI of n order matrix
Seek consistency ratio CR=CI/RI
If CR > 0.1, each Small object consistency is poor in judgment matrix H, needs to reconfigure judgment matrix.
If CR≤0.1, each Small object consistency is good in judgment matrix H.
Pass through by consistency check, obtains index weights computational chart.
Step S3, quantizating index, the overall development in conjunction with current intelligence manufacture maturity is horizontal, by the development level of index
Unified to use a kind of dimension, quantitative criteria defines value by the following several types value in intelligence manufacture process of construction to determine:
The standard reference point or domestic and international generally acknowledged value that set both at home and abroad or current value outstanding both at home and abroad.It is given below three in the present embodiment
Grade index X111The quantizing process of product design: carry out computer assisted two-dimensional design based on design experiences, and formulate product design
Specification obtains 30 points；It realizes the collaboration inside computer-aided three-dimensional design and product design, obtains 50 points；Building collection
At the threedimensional model of product design information, the design and simulation optimization of key link is carried out, realizes product design and technological design
Concurrent collaborative scores 70 marks；Knowledge based library realizes that design technology manufactures full dimension simulation and optimization, and realizes based on model
The collaboration of the business such as design, manufacture, inspection, O&M, obtains 90 points；Realize the product design cloud service based on big data, knowledge base,
It realizes personalization of product design, collaborative design, gets a mark of 100.
Step S4, fuzzy overall evaluation, the present embodiment are commented according to the quantization of the step S2 weight determined and step 3 index
Point, maturity grade of evaluation object during intelligence manufacture is obtained using the method for fuzzy overall evaluation, and step S4 is into one
Step includes following sub-step:
S4.1, evaluation approach domain is formulated
Five grades (planning grade, integrated grade, optimization level, leads grade at specification grade) of intelligence manufacture capability maturity are straight
The grade label being set as in Comment gathers is connect, determines grade of the fuzzy subset in Comment gathers using abstract classification, it is corresponding every
A grade has corresponding quantization marking, and a reference value is set as V={ v1,v2,v3,v4,v5}={ 20,40,60,80,100 }.
S4.2, building fuzzy relation matrix
The score for evaluating data and evaluate collection { 20,40,60,80,100 } are subjected to difference operation, each finger is calculated
Mark adjusts the distance with the distance between evaluate collection and does derivative action, and then be standardized to inverse, obtain corresponding index not
With the degree of membership in evaluate collection, fuzzy relation matrix is constructed.
S4.3, fuzzy overall evaluation result vector is calculated
Weight vector and fuzzy relation matrix are synthesized with the algorithm of fuzzy mathematics, is calculated and is accordingly evaluated pair
The Result of Fuzzy Comprehensive Evaluation vector of elephant, concrete operations are showed themselves in that the mould of three-level index weights operator and each assessment grade
Paste relationship column vector is multiplied, and obtains the degree of membership of two-level index；
S4.4, Calculation Estimation object score
It is multiplied the corresponding degree of membership of the weight operator of two-level index to obtain first class index degree of membership；First class index power
Weight membership vector corresponding with its, which is multiplied, can be obtained evaluation score.
S4.5, evaluation object is classified
According to the class criteria defined to intelligence manufacture, pass through energy locating for evaluation object score you can get it intelligence manufacture
Power grade.
As can be seen from the above description, the embodiment of the present invention has the following beneficial effects:
1, the intelligence manufacture capability maturity evaluation side based on Fuzzy AHP provided through the embodiment of the present invention
Method, foundation evaluation purpose,
By the mode of investigation and expert consulting, the intelligence manufacture capability maturity evaluation index being layered step by step is established
System；By the intelligence manufacture Heuristics of expert, the index power of assessment indicator system is accurately obtained by analytic hierarchy process (AHP)
Weight, finally obtains the score of evaluation object using the method for fuzzy synthesis.This method introduces a large amount of special in evaluation procedure
Family's Heuristics, and binding hierarchy analytic approach reduces the subjectivity of expert estimation so that evaluation result it is more objective, it is true,
It is credible.
2, the intelligence manufacture capability maturity evaluation side based on Fuzzy AHP provided through the embodiment of the present invention
Method evaluates intelligence manufacture ability rating using analytic hierarchy process (AHP), be by qualitative evaluation quantification, it is more scientific.
3, the intelligence manufacture capability maturity evaluation side based on Fuzzy AHP provided through the embodiment of the present invention
Method, evaluation procedure can more sequencing by developing simple computer appraisal tool can substantially reduce implementation personnel
Workload.
Those of ordinary skill in the art will appreciate that: realize that all or part of the steps of above method embodiment can pass through
Simple computer program is developed to complete, on the portable computer that program above-mentioned can be installed, the program when being executed,
Execute step including the steps of the foregoing method embodiments.
Finally, it should be noted that the foregoing is merely presently preferred embodiments of the present invention, it is merely to illustrate skill of the invention
Art scheme, is not intended to limit the scope of the present invention.Any modification for being made all within the spirits and principles of the present invention,
Equivalent replacement, improvement etc., are included within the scope of protection of the present invention.
Claims (6)
1. the intelligence manufacture capability maturity evaluation method based on Fuzzy AHP, which is characterized in that this method includes such as
Lower step:
S1, establish assessment indicator system: according to evaluation purpose, by the mode of investigation and expert consulting, foundation divides step by step
The intelligence manufacture capability maturity assessment indicator system of layer；
S2, it determines weight: using analytic hierarchy process (AHP), introducing the review comment of domain expert, determine its same each index of level
Weight；
S3, quantizating index: the overall development in conjunction with current intelligence manufacture maturity is horizontal, by the unified use of the development level of index
A kind of dimension；
S4, fuzzy overall evaluation: according to a reference value of Comment gathers and corresponding evaluation approach collection, the person in servitude of evaluate collection fuzzy subset is obtained
Category degree constructs fuzzy relation matrix；According to the weight vectors and fuzzy relation matrix of index, maturation is obtained using weighted mean method
The total score of degree, and then judge maturity levels locating for evaluation object.
2. the intelligence manufacture capability maturity evaluation method according to claim 1 based on Fuzzy AHP, special
Sign is that step S1 further comprises following sub-step:
S1.1, foundation evaluation purpose, establish by the mode of investigation and expert consulting by top, middle layer and most bottom
3 layers of intelligence manufacture capability maturity assessment indicator system of layer composition；
S1.2, meaning representated by each layer is defined, top is the final goal for needing to obtain, i.e. intelligence manufacture ability is mature
Degree；Middle layer is top and the bottom relationship tie；The bottom is specifically to implement means and method in manufacturing process.
3. the intelligence manufacture capability maturity evaluation method according to claim 1 based on Fuzzy AHP, special
Sign is that step S2 further comprises following sub-step:
S2.1, Judgement Matricies H
The element of judgment matrix is the evaluation of estimate of the two indexes relative importance obtained using 1-9 scaling law, and evaluation of estimate is by inviting
Please intelligence manufacture domain expert give a mark, scoring process is mutually indepedent；
S2.2, characteristic vector W=[ω is calculated1,ω2,L,wn]
The every row element of judgment matrix H is carried out even multiplied to Mi, then calculate MiN times rootAcquire weight
S2.3, consistency check
If consistency ratio CR > 0.1, illustrate that each goal congruence is poor in judgment matrix H, needs to reconfigure；If CR≤0.1,
Illustrate that each goal congruence is preferable in judgment matrix H, W is required matrix.
4. the intelligence manufacture capability maturity evaluation method according to claim 1 based on Fuzzy AHP,
It is characterized in that, the score equivalent of evaluation index is set both at home and abroad at hundred-mark system, conversion process sufficiently foundation in step S3
Standard reference point generally acknowledges value or current value outstanding both at home and abroad both at home and abroad, and by industry field expertise.
5. the intelligence manufacture capability maturity evaluation method according to claim 1 based on Fuzzy AHP,
It is characterized in that, step S4 further comprises following sub-step:
S4.1, evaluation approach domain is formulated
Five grades (planning grade, integrated grade, optimization level, leads grade at specification grade) of intelligence manufacture capability maturity are directly set
The grade label being set in Comment gathers determines grade of the fuzzy subset in Comment gathers using abstract classification, corresponds to each etc.
Grade has corresponding quantization marking, and a reference value is set as V={ v1,v2,v3,v4,v5}={ 20,40,60,80,100 }；
S4.2, building fuzzy relation matrix
The score for evaluating data is made the difference with evaluate collection, each index is calculated with the distance between evaluate collection, takes falling for distance
Number is standardized operation, obtains the degree of membership that corresponding index is concentrated in different evaluation, obtains fuzzy relation matrix；
S4.3, fuzzy overall evaluation result vector is calculated
Weight vector and fuzzy relation matrix are synthesized with the algorithm of fuzzy mathematics, is calculated and is accordingly evaluated object
Result of Fuzzy Comprehensive Evaluation vector；
S4.4, corresponding index score is calculated according to fuzzy overall evaluation result
By evaluate collection and the fuzzy membership of corresponding index, the corresponding score of two-level index is obtained；
S4.5, evaluation object is classified according to first class index score
In evaluation object classification process, according to first class index weight and first class index Calculation Estimation subject evaluation total score, and root
According to evaluate collection grade scale, judge which kind of rank it reaches.
6. consistency ratio CR according to claim 3, which is characterized in that the formula of seeking of consistency ratio is CR=
CI/RI.Wherein CI=(λmax- n)/(n-1), λmaxFor the Maximum characteristic root of judgment matrix H, n is the order of judgment matrix H；RI
For the random consistency index of n rank matrix.
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2018
- 2018-07-12 CN CN201810764010.0A patent/CN109063976A/en not_active Withdrawn
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