CN108256763A - Nonstandard components supplying quotient manufacturing capacity analysis method and device based on analytic hierarchy process (AHP) - Google Patents
Nonstandard components supplying quotient manufacturing capacity analysis method and device based on analytic hierarchy process (AHP) Download PDFInfo
- Publication number
- CN108256763A CN108256763A CN201810036788.XA CN201810036788A CN108256763A CN 108256763 A CN108256763 A CN 108256763A CN 201810036788 A CN201810036788 A CN 201810036788A CN 108256763 A CN108256763 A CN 108256763A
- Authority
- CN
- China
- Prior art keywords
- analysis indexes
- analysis
- grade
- indexes
- manufacturing capacity
- 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.)
- Pending
Links
- 238000004458 analytical method Methods 0.000 title claims abstract description 284
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 65
- 238000000034 method Methods 0.000 title claims abstract description 57
- 239000011159 matrix material Substances 0.000 claims abstract description 70
- 238000011156 evaluation Methods 0.000 claims description 22
- 238000010606 normalization Methods 0.000 claims description 10
- 238000003908 quality control method Methods 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 4
- 238000004422 calculation algorithm Methods 0.000 claims description 3
- 238000013068 supply chain management Methods 0.000 claims description 3
- 238000005516 engineering process Methods 0.000 description 5
- 239000000463 material Substances 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000010276 construction Methods 0.000 description 2
- 238000003860 storage Methods 0.000 description 2
- 101150042248 Mgmt gene Proteins 0.000 description 1
- 239000003795 chemical substances by application Substances 0.000 description 1
- 150000001875 compounds Chemical class 0.000 description 1
- 238000000205 computational method Methods 0.000 description 1
- 238000003754 machining Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000011158 quantitative evaluation Methods 0.000 description 1
- 238000004064 recycling Methods 0.000 description 1
- 238000012384 transportation and delivery Methods 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/04—Manufacturing
-
- 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
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Educational Administration (AREA)
- Marketing (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Manufacturing & Machinery (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention discloses a kind of nonstandard components supplying quotient manufacturing capacity analysis method for being based on analytic hierarchy process (AHP) and device, this method include：Creation analysis achievement data library, including several analysis indexes grades and corresponding analysis indexes；Party in request's demand structure assessment models are obtained, including several analysis indexes grades and analysis indexes；Analysis indexes measure of importance is carried out step by step to the analysis indexes grade two-by-two to compare；To analysis indexes grade creation analysis index judgment matrix, and judge that it meets the condition of acceptable consistency step by step, obtain the score by rules of each analysis indexes and score and weight to obtain effect score value；The effect score value of each analysis indexes is added to obtain the final assessment point of each supplier；The final assessment point of each supplier is ranked up by ordering rule.The present invention selects corresponding assessment models rapidly and accurately to be judged by prior creation analysis achievement data library, according to demand square concrete condition, promotes the accuracy and speed of supplier's assessment.
Description
Technical field
This application involves computer analytical technology fields, and nonstandard the zero of analytic hierarchy process (AHP) is based on more particularly to a kind of
Parts suppliers manufacturing capacity analytical equipment.
Background technology
It, often need to be to the processing producer of parts after party in request proposes parts machining demand in supply chain field
Manufacturing capacity assessed, usual way be processing producer manufacturing capacity from single dimension carry out quantitative evaluation；Or
It is simply comprehensive into its value of assessment from several dimensions.For example, for some nonstandard parts, to each processing producer
Manufacturing capacity assessed.
Currently existing scheme has Split Method and simple compound weight method.Several analysis indexes are separated progress by Split Method
Assessment comparison.Such as working ability and price are assessed, and several results are ranked up and compare its quality.It is simple comprehensive
Analysis indexes are carried out a series of decompose and scored by weighting method, then integrate to obtain the manufacturing capacity impact factor by simple weighted
Comprehensive score；And so on, other analysis indexes will also obtain final scoring, then be ranked up comparison, and assessment is optimal
Popularization manufacturing capacity impact factor.
But both schemes have the disadvantages that：1) nondimensionalizations：The scoring of existing manufacturing capacity impact factor is all
Be calculated its quantitative value based on absolute magnitude or relative quantity, and different manufacturing capacity impact factor quantity, unit quantity
Change having differences（I.e. the order of magnitude is different, and there is no comparativity and the scale calculated are inconsistent for different data levels）.2).
It is not accurate enough：Different manufacturing capacity impact factors show different effects in each index, if simply to each index
Score or take a certain index to be compared after only assigning a weighted value weighting, it is not accurate enough, it is impossible to effectively to assess optimal
Manufacturing capacity impact factor is simultaneously promoted.3) recycling rates of waterused are not high, and evaluation structure arbitrariness is strong, for different demands
Fang Jinhang is individually assessed, and the visualization utilization rate for assessing data is not high.
Invention content
The purpose of the application is, provides a kind of more science, the accurately nonstandard parts confession based on analytic hierarchy process (AHP)
Answer quotient's manufacturing capacity analytical equipment.
One of the objects of the present invention is to provide a kind of nonstandard components supplying quotient manufacturing capacities based on analytic hierarchy process (AHP)
Analysis method, which is characterized in that this method includes：
Structure evaluates the analysis indexes database of nonstandard components supplying quotient manufacturing capacity, point in the analysis indexes database
Analysis index is divided into several analysis indexes grades, and each analysis indexes grade includes several analysis indexes；
Demand structure assessment models of the party in request to nonstandard components supplying quotient manufacturing capacity are obtained, and by the demand with analyzing
Analysis indexes in achievement data library are matched step by step, screen or rebuild the analysis indexes grade of party in request and each analysis
The analysis indexes of index grade, and newly-increased analysis indexes are stored in the analysis indexes database；
Analysis indexes measure of importance is carried out step by step to the analysis indexes grade two-by-two to compare；
Build the analysis indexes judgment matrix for evaluating nonstandard components supplying quotient manufacturing capacity step by step to the analysis indexes grade, and
Judge that it meets the condition of acceptable consistency；
It obtains the score by rules of each analysis indexes and scores and weight to obtain effect score value；
The effect score value of each analysis indexes is added to obtain the final assessment point of each supplier；
The final assessment point of each supplier is ranked up by ordering rule.
Further, the present invention is based in the nonstandard components supplying quotient manufacturing capacity analysis method of analytic hierarchy process (AHP), institute
It states analysis indexes measure of importance natural number 1 to 9 to represent, 1 represents one of them in two analysis indexes being compared to each other
Analysis indexes relative importance for another analysis indexes is identical, and 9 represent in two factors being compared to each other
One of analysis indexes relative importance for another analysis indexes is maximum, on the contrary then represented with inverse.
Further, the present invention is based in the nonstandard components supplying quotient manufacturing capacity analysis method of analytic hierarchy process (AHP), institute
It states and judges that the method for the condition that judgment matrix meets acceptable consistency is as follows：
A:The analysis indexes are carried out with judgment matrix normalized step by step, normalized method is to will determine that matrix each column is asked
With, and calculate per the ratio of column data in the summation；
B:To the weight of average, as each analysis indexes of supplier is calculated in the judgment matrix after normalization per a line；
C:Calculate the approximate solution of feature vector；
D:Calculate the Maximum characteristic root of the judgment matrix；
E:Calculate the coincident indicator value of the judgment matrix；
F:Confirm Aver-age Random Consistency Index RI；
G:Calculate the random consistency ration of the judgment matrix；
H:Judge that the judgment matrix meets acceptable condition for consistence；
I:According to analysis indexes in each analysis indexes grade of analysis indexes grade step-by-step calculation to the weight coefficient of overall performane, so as to obtain
Go out the weight table that supplier selects evaluation index, wherein whole analysis indexes are to the weight system of general objective in each analysis indexes grade
The sum of number is 1.
Further, it the present invention is based in the nonstandard components supplying quotient manufacturing capacity analysis method of analytic hierarchy process (AHP), incites somebody to action
In weight coefficient, each most subordinate's analysis indexes grade in each analysis indexes grade in each analysis indexes grade corresponding to analysis indexes
Each analysis indexes correspond to the weight coefficient of general objective, score by rules and score value at least are set up to each most subordinate analysis indexes,
And several check items are segmented to each score by rules, reach and then obtain corresponding scoring, reach it is poor or without relative recording, then
Be scored at 0, obtain nonstandard components supplying quotient all the effect score value of most subordinate's analysis indexes and sum, sorting obtains nonstandard zero
Parts suppliers manufacturing capacity sorts.
Another object of the present invention is to provide a kind of nonstandard components supplying quotient manufacturing capacity based on analytic hierarchy process (AHP)
Analytical equipment, the device include：
Analysis indexes database module for obtaining analysis indexes, and stores analysis indexes grade and each analysis indexes grade
Analysis indexes；
Assessment models build module, and square demand structure assessment models, the assessment models include default assessment models according to demand
With personalized assessment models, the default assessment models and personalized assessment models include several analysis indexes grades and each analysis
The analysis indexes of index grade；
Weight coefficient generation module, for building the measure of importance of analysis indexes in each analysis indexes grade two-by-two to comparator matrix
Table calculates in each analysis indexes grade each analysis indexes to the weight coefficient corresponding to higher level's analysis indexes according to normalization algorithm,
And including at least each analysis indexes in most subordinate's analysis indexes grade to the weight coefficient corresponding to overall performane；
Effect score value generation module, for obtaining the weight coefficient of each analysis indexes and each confession in most subordinate's analysis indexes grade
The scoring of each analysis indexes in the most subordinate analysis indexes grade corresponding to quotient is answered, respectively analyzes and refers in calculating most subordinate's analysis indexes grade
Target effect score value；
Assessment result acquisition module, for the effect score value of whole analysis indexes in most subordinate's analysis indexes grade to be added to obtain
The final assessment point of each supplier.
Further, the present invention is based in the nonstandard components supplying quotient manufacturing capacity analytical equipment of analytic hierarchy process (AHP), institute
Weight coefficient generation module is stated to include：
Comparator matrix table structure module two-by-two, with analysis indexes grade, creation analysis index is described two-by-two to comparing matrix table step by step
Matrix element be in matrix table two analysis indexes corresponding with the matrix element two-by-two compared with obtain after relative importance
Relatively important coefficient.
Further, the present invention is based in the nonstandard components supplying quotient manufacturing capacity analytical equipment of analytic hierarchy process (AHP), institute
Weight coefficient generation module is stated to further comprise：
Module is normalized, for by the phase in the sub-goal layer pairwise comparison matrix table and indicator layer pairwise comparison matrix table
Significant coefficient is normalized by row；
Summation module, for the analysis indexes grade after normalization comparator matrix table and indicator layer pairwise comparison matrix table two-by-two
Again by row summation, feature vector is obtained；
Weight computation module, for by the total quantity of described eigenvector divided by higher level's analysis indexes, obtaining each analysis indexes grade
In each analysis indexes grade analysis indexes corresponding to weight coefficient and each weight coefficient.
Further, the present invention is based in the nonstandard components supplying quotient manufacturing capacity analytical equipment of analytic hierarchy process (AHP), institute
Assessment result acquisition module is stated to include：
Sorting module, for the final assessment point sequence of each analysis indexes of several suppliers to be obtained supplier's manufacturing capacity
Sequence.
Further, the present invention is based in the nonstandard components supplying quotient manufacturing capacity analytical equipment of analytic hierarchy process (AHP), institute
Commentary estimates model construction module and includes integrally requiring point of creation analysis index grade and each analysis indexes grade according to buying industry
Analyse index, for party in request carry out fuzzy evaluation judgement, the analysis indexes include quality control, technical capability, availability, into
The combination of one or more of this control and flexibility ratio；The personalized customization type assessment models are square specific as desired
It is required that the analysis indexes of parameter creation analysis index grade and each analysis indexes grade.
Further, the present invention is based in the nonstandard components supplying quotient manufacturing capacity analytical equipment of analytic hierarchy process (AHP), institute
Between stating several new suppliers that supplier can be party in request, to find the supplier met the requirements；It may be party in request
Several new suppliers and several existing suppliers, to improve supplier's inventory, promote party in request's supply chain management efficiency.
Advantageous effect, relative to the prior art, the present invention is by prior creation analysis achievement data library and using a variety of
Assessment models assess nonstandard components supplying quotient, according to demand square concrete condition select corresponding assessment models into
Row rapidly and accurately judges, promotes the accuracy and speed of supplier's assessment.The nonstandard components supplying quotient manufacture specifically provided
Capability analysis method by the overall performane for influencing the impact factor of nonstandard components supplying quotient manufacturing capacity by being decomposed into multiple points
Index (establishing analysis indexes grade) is analysed, and then each subordinate's analysis indexes grade is decomposed into subordinate's analysis indexes grade again again, is built
The table of comparator matrix two-by-two of each analysis indexes grade obtains the weight coefficient of each analysis indexes, then further according to most subordinate of each supplier
The effect score value and corresponding weight coefficient of analysis indexes, the obtained effect score value of whole most subordinate's analysis indexes finally will
All the effect score value of most subordinate's analysis indexes is added to obtain the final assessment point of each supplier for each supplier.Due to the above method
On the whole based on analytic hierarchy process (AHP), therefore assessment result can more science, accurate.
Description of the drawings
Fig. 1 is the flow signal of the nonstandard components supplying quotient manufacturing capacity analysis method the present invention is based on analytic hierarchy process (AHP)
Figure.
Fig. 2 is the structural representation of the nonstandard components supplying quotient manufacturing capacity analytical equipment the present invention is based on analytic hierarchy process (AHP)
Figure.
Fig. 3 selects evaluation criterion weight table for new supplier of 5 party in request of table of the embodiment of the present invention.
Fig. 4 is 6 supplier's grade form of table of the embodiment of the present invention.
Specific embodiment
For further illustrate the present invention to reach technological means and the effect that predetermined goal of the invention is taken, with reference to Fig. 1-
4 detailed description are as follows.
A kind of nonstandard components supplying quotient manufacturing capacity analysis method based on analytic hierarchy process (AHP), which is characterized in that the party
Method includes：
Structure evaluates the analysis indexes database of nonstandard components supplying quotient manufacturing capacity, point in the analysis indexes database
Analysis index is divided into several analysis indexes grades, and each analysis indexes grade includes several analysis indexes；
Demand structure assessment models of the party in request to nonstandard components supplying quotient manufacturing capacity are obtained, and by the demand with analyzing
Analysis indexes in achievement data library are matched step by step, screen or rebuild the analysis indexes grade of party in request and each analysis
The analysis indexes of index grade, and newly-increased analysis indexes are stored in the analysis indexes database；
Analysis indexes measure of importance is carried out step by step to the analysis indexes grade two-by-two to compare；
Build the analysis indexes judgment matrix for evaluating nonstandard components supplying quotient manufacturing capacity step by step to the analysis indexes grade, and
Judge that it meets the condition of acceptable consistency；
It obtains the score by rules of each analysis indexes and scores and weight to obtain effect score value；
The effect score value of each analysis indexes is added to obtain the final assessment point of each supplier；
The final assessment point of each supplier is ranked up by ordering rule.
Further, the present invention is based in the nonstandard components supplying quotient manufacturing capacity analysis method of analytic hierarchy process (AHP), institute
It states analysis indexes measure of importance natural number 1 to 9 to represent, 1 represents one of them in two analysis indexes being compared to each other
Analysis indexes relative importance for another analysis indexes is identical, and 9 represent in two factors being compared to each other
One of analysis indexes relative importance for another analysis indexes is maximum, on the contrary then represented with inverse.
Further, the present invention is based in the nonstandard components supplying quotient manufacturing capacity analysis method of analytic hierarchy process (AHP), institute
It states and judges that the method for the condition that judgment matrix meets acceptable consistency is as follows：
A:The analysis indexes are carried out with judgment matrix normalized step by step, normalized method is to will determine that matrix each column is asked
With, and calculate per the ratio of column data in the summation；
B:To the weight of average, as each analysis indexes of supplier is calculated in the judgment matrix after normalization per a line；
C:Calculate the approximate solution of feature vector；
D:Calculate the Maximum characteristic root of the judgment matrix；
E:Calculate the coincident indicator value of the judgment matrix；
F:Confirm Aver-age Random Consistency Index RI；
G:Calculate the random consistency ration of the judgment matrix；
H:Judge that the judgment matrix meets acceptable condition for consistence；
I:According to analysis indexes in each analysis indexes grade of analysis indexes grade step-by-step calculation to the weight coefficient of overall performane, so as to obtain
Go out the weight table that supplier selects evaluation index, wherein whole analysis indexes are to the weight system of general objective in each analysis indexes grade
The sum of number is 1.
Further, it the present invention is based in the nonstandard components supplying quotient manufacturing capacity analysis method of analytic hierarchy process (AHP), incites somebody to action
In weight coefficient, each most subordinate's analysis indexes grade in each analysis indexes grade in each analysis indexes grade corresponding to analysis indexes
Each analysis indexes correspond to the weight coefficient of general objective, score by rules and score value at least are set up to each most subordinate analysis indexes,
And several check items are segmented to each score by rules, reach and then obtain corresponding scoring, reach it is poor or without relative recording, then
Be scored at 0, obtain nonstandard components supplying quotient all the effect score value of most subordinate's analysis indexes and sum, sorting obtains nonstandard zero
Parts suppliers manufacturing capacity sorts.
Another object of the present invention is to provide a kind of nonstandard components supplying quotient manufacturing capacity based on analytic hierarchy process (AHP)
Analytical equipment, the device include：
Analysis indexes database module for obtaining analysis indexes, and stores analysis indexes grade and each analysis indexes grade
Analysis indexes；
Assessment models build module, and square demand structure assessment models, the assessment models include default assessment models according to demand
With personalized assessment models, the default assessment models and personalized assessment models include several analysis indexes grades and each analysis
The analysis indexes of index grade；
Weight coefficient generation module, for building the measure of importance of analysis indexes in each analysis indexes grade two-by-two to comparator matrix
Table calculates in each analysis indexes grade each analysis indexes to the weight coefficient corresponding to higher level's analysis indexes according to normalization algorithm,
And including at least each analysis indexes in most subordinate's analysis indexes grade to the weight coefficient corresponding to overall performane；
Effect score value generation module, for obtaining the weight coefficient of each analysis indexes and each confession in most subordinate's analysis indexes grade
The scoring of each analysis indexes in the most subordinate analysis indexes grade corresponding to quotient is answered, respectively analyzes and refers in calculating most subordinate's analysis indexes grade
Target effect score value；
Assessment result acquisition module, for the effect score value of whole analysis indexes in most subordinate's analysis indexes grade to be added to obtain
The final assessment point of each supplier.
Further, the present invention is based in the nonstandard components supplying quotient manufacturing capacity analytical equipment of analytic hierarchy process (AHP), institute
Weight coefficient generation module is stated to include：
Comparator matrix table structure module two-by-two, with analysis indexes grade, creation analysis index is described two-by-two to comparing matrix table step by step
Matrix element be in matrix table two analysis indexes corresponding with the matrix element two-by-two compared with obtain after relative importance
Relatively important coefficient.
Further, the present invention is based in the nonstandard components supplying quotient manufacturing capacity analytical equipment of analytic hierarchy process (AHP), institute
Weight coefficient generation module is stated to further comprise：
Module is normalized, for by the phase in the sub-goal layer pairwise comparison matrix table and indicator layer pairwise comparison matrix table
Significant coefficient is normalized by row；
Summation module, for the analysis indexes grade after normalization comparator matrix table and indicator layer pairwise comparison matrix table two-by-two
Again by row summation, feature vector is obtained；
Weight computation module, for by the total quantity of described eigenvector divided by higher level's analysis indexes, obtaining each analysis indexes grade
In each analysis indexes grade analysis indexes corresponding to weight coefficient and each weight coefficient.
Further, the present invention is based in the nonstandard components supplying quotient manufacturing capacity analytical equipment of analytic hierarchy process (AHP), institute
Assessment result acquisition module is stated to include：
Sorting module, for the final assessment point sequence of each analysis indexes of several suppliers to be obtained supplier's manufacturing capacity
Sequence.
Further, the present invention is based in the nonstandard components supplying quotient manufacturing capacity analytical equipment of analytic hierarchy process (AHP), institute
Commentary estimates model construction module and includes integrally requiring point of creation analysis index grade and each analysis indexes grade according to buying industry
Analyse index, for party in request carry out fuzzy evaluation judgement, the analysis indexes include quality control, technical capability, availability, into
The combination of one or more of this control and flexibility ratio；The personalized customization type assessment models are square specific as desired
It is required that the analysis indexes of parameter creation analysis index grade and each analysis indexes grade.
Further, the present invention is based in the nonstandard components supplying quotient manufacturing capacity analytical equipment of analytic hierarchy process (AHP), institute
Between stating several new suppliers that supplier can be party in request, to find the supplier met the requirements；It may be party in request
Several new suppliers and several existing suppliers, to improve supplier's inventory, promote party in request's supply chain management efficiency.
The present invention is using the alternative supplier of the strategic type material of party in request's searching as specific implementation case to supplier evaluation
System module and evaluation method are described in detail as follows：Party in request needs two operating bed key components and parts, main support hand
Art bed agent structure has the requirement of very high safe class, belongs to typical strategic type material, is mainly supplied by A suppliers and B
Shang Liangjia suppliers is answered to cooperate.Wherein, during cooperating with B suppliers, Quality Mgmt Dept and material plan portion are constantly fed back
Its quality and delivery problems, especially have two inferior qualities it is bad caused by stop line so that party in request have to by script sea-freight
Cargo makes urgent air transport into, cause it is branched go out nearly 200,000 air freight.Therefore party in request also intends to find new supplier replacement B
Supplier.
Square demand screens quality control, technology energy to evaluation group of party in request from analysis indexes database according to demand first
The analysis indexes of power, availability, cost control and flexibility ratio level-one analysis indexes and two-level index as party in request, utilize nine
Quality control, technical capability, availability, cost control and flexibility ratio are compared in point-score measurement two-by-two, construct suitable
Mai Ke only company actual situations and analysis indexes judgment matrix table：Wherein 1 analysis indexes metric table of table is as follows：
By the participation of expert team, the judgment matrix of 5 indexs of new supplier evaluation is as follows, refers to table 2 and newly supplies
Quotient evaluates first class index judgment matrix table：
2 new supplier evaluation first class index judgment matrix table of table is normalized.Normalized method is will to sentence
Disconnected matrix each column summation, and calculate per the ratio of column data in the summation.Formula is as follows：bij=bij/bij(i,j=1, 2,
3...n),
It is as follows according to the normalization result of calculation of formula：
Calculate the approximate solution of feature vector：
Calculate the Maximum characteristic root of judgment matrix：
Calculate the coincident indicator value of judgment matrix：
It is checked according to 3 Aver-age Random Consistency Index of following table table, RI=1.12,
Calculate the random consistency ration of judgment matrix：
The weight of corresponding 5 level-one evaluation indexes selects evaluation first class index to refer to new supplier of 4 party in request of following table table
Shown in weight：
Second step：The judgment matrix of two-level index under 5 first class index respectively, and judge that it meets acceptable consistency
Condition, with reference to the judgment matrix of first class index and the computational methods of weight and first class index consistency desired result process, similarly may be used
To obtain the two-level index weight judging result under quality control.
Third walks：According to first class index weight and two-level index weight, weight of the two-level index to general objective is calculated.So as to
Show that new supplier of Mai Ke only companies selects the weight table of evaluation index in detail as shown in Figure 3（The new supplier's selection of 5 party in request of table
Evaluation criterion weight table）.
Formulate the score by rules that new supplier selects evaluation index：In order to which new supplier is allowed to select evaluation index with more behaviour
The property made, comprehensive industry characteristic and party in request's demand, expert team set up score by rules for 19 two-level index.Each two level
Target setting is 10 points, and segments several check items and scoring criterion.Project, which is reached, then obtains corresponding scoring, reach it is poor or
Person does not have relative recording, then is scored at 0, and evaluation result is in detail as shown in Figure 4（6 supplier's grade form of table）.
According to evaluation result, A, C, F supplier score are all higher than the score 5.73 of B suppliers.Therefore evaluation group is recommended
B suppliers are eliminated, and selects C suppliers as supplier is substituted and is cultivated.This result and party in request's demand expection kissing
It closes.
Advantageous effect, relative to the prior art, the present invention is by prior creation analysis achievement data library and using a variety of
Assessment models assess nonstandard components supplying quotient, according to demand square concrete condition select corresponding assessment models into
Row rapidly and accurately judges, promotes the accuracy and speed of supplier's assessment.The nonstandard components supplying quotient manufacture specifically provided
Capability analysis method by the overall performane for influencing the impact factor of nonstandard components supplying quotient manufacturing capacity by being decomposed into multiple points
Index (establishing analysis indexes grade) is analysed, and then each subordinate's analysis indexes grade is decomposed into subordinate's analysis indexes grade again again, is built
The table of comparator matrix two-by-two of each analysis indexes grade obtains the weight coefficient of each analysis indexes, then further according to most subordinate of each supplier
The effect score value and corresponding weight coefficient of analysis indexes, the obtained effect score value of whole most subordinate's analysis indexes finally will
All the effect score value of most subordinate's analysis indexes is added to obtain the final assessment point of each supplier for each supplier.Due to the above method
On the whole based on analytic hierarchy process (AHP), therefore assessment result can more science, accurate.
One of ordinary skill in the art will appreciate that hardware can be passed through by realizing all or part of step of above-described embodiment
It completes, relevant hardware can also be instructed to complete by program, the program can be stored in a kind of computer-readable
In storage medium, storage medium mentioned above can be read-only memory, disk or CD etc..
The above is only the preferred embodiment of the application, not makees limitation in any form to the application, though
Right the application is disclosed above with preferred embodiment, however is not limited to the application, any technology people for being familiar with this profession
Member, is not departing from the range of technical scheme, when the technology contents using the disclosure above make a little change or modification
For the equivalent embodiment of equivalent variations, as long as being the technical spirit pair according to the application without departing from technical scheme content
Any simple modification, equivalent change and modification that above example is made, in the range of still falling within technical scheme.
Claims (10)
- A kind of 1. nonstandard components supplying quotient manufacturing capacity analysis method based on analytic hierarchy process (AHP), which is characterized in that this method Including：Structure evaluates the analysis indexes database of nonstandard components supplying quotient manufacturing capacity, point in the analysis indexes database Analysis index is divided into several analysis indexes grades, and each analysis indexes grade includes several analysis indexes；Demand structure assessment models of the party in request to nonstandard components supplying quotient manufacturing capacity are obtained, and by the demand with analyzing Analysis indexes in achievement data library are matched step by step, screen or rebuild the analysis indexes grade of party in request and each analysis The analysis indexes of index grade, and newly-increased analysis indexes are stored in the analysis indexes database；Analysis indexes measure of importance is carried out step by step to the analysis indexes grade two-by-two to compare；Build the analysis indexes judgment matrix for evaluating nonstandard components supplying quotient manufacturing capacity step by step to the analysis indexes grade, and Judge that it meets the condition of acceptable consistency；It obtains the score by rules of each analysis indexes and scores and weight to obtain effect score value；The effect score value of each analysis indexes is added to obtain the final assessment point of each supplier；The final assessment point of each supplier is ranked up by ordering rule.
- 2. the nonstandard components supplying quotient manufacturing capacity analysis method based on analytic hierarchy process (AHP) as described in claim 1, special Sign is：The analysis indexes measure of importance natural number 1 to 9 represents that 1 represents in two analysis indexes being compared to each other One of analysis indexes for another analysis indexes relative importance it is identical, 9 represent be compared to each other two One of analysis indexes in a factor relative importance for another analysis indexes is maximum, it is on the contrary then with falling Number represents.
- 3. the nonstandard components supplying quotient manufacturing capacity analysis method according to claim 2 based on analytic hierarchy process (AHP), It is characterized in that, the method for the condition for judging the acceptable consistency of judgment matrix satisfaction is as follows：A:The analysis indexes are carried out with judgment matrix normalized step by step, normalized method is to will determine that matrix each column is asked With, and calculate per the ratio of column data in the summation；B:To the weight of average, as each analysis indexes of supplier is calculated in the judgment matrix after normalization per a line；C:Calculate the approximate solution of feature vector；D:Calculate the Maximum characteristic root of the judgment matrix；E:Calculate the coincident indicator value of the judgment matrix；F:Confirm Aver-age Random Consistency Index RI；G:Calculate the random consistency ration of the judgment matrix；H:Judge that the judgment matrix meets acceptable condition for consistence；I:According to analysis indexes in each analysis indexes grade of analysis indexes grade step-by-step calculation to the weight coefficient of overall performane, so as to obtain Go out the weight table that supplier selects evaluation index, wherein whole analysis indexes are to the weight system of general objective in each analysis indexes grade The sum of number is 1.
- 4. the nonstandard components supplying quotient manufacturing capacity analysis method based on analytic hierarchy process (AHP) as claimed in claim 3, special Sign is：By corresponding to analysis indexes in analysis indexes grade each in each analysis indexes grade weight coefficient, respectively most descend fraction Each analysis indexes in analysis index grade correspond to the weight coefficient of general objective, and it is thin that at least each most subordinate analysis indexes are set up with scoring Then and score value, and to each score by rules several check items are segmented, reaches and then obtain corresponding scoring, reached poor or without phase Record is closed, then is scored at 0, obtain the effect score value of the whole most subordinate's analysis indexes of nonstandard components supplying quotient and sums, sort Obtain nonstandard components supplying quotient manufacturing capacity sequence.
- A kind of 5. nonstandard components supplying quotient manufacturing capacity analytical equipment based on analytic hierarchy process (AHP), which is characterized in that the device Including：Analysis indexes database module for obtaining analysis indexes, and stores analysis indexes grade and each analysis indexes grade Analysis indexes；Assessment models build module, and square demand structure assessment models, the assessment models include default assessment models according to demand With personalized assessment models, the default assessment models and personalized assessment models include several analysis indexes grades and each analysis The analysis indexes of index grade；Weight coefficient generation module, for building the measure of importance of analysis indexes in each analysis indexes grade two-by-two to comparator matrix Table calculates in each analysis indexes grade each analysis indexes to the weight coefficient corresponding to higher level's analysis indexes according to normalization algorithm, And including at least each analysis indexes in most subordinate's analysis indexes grade to the weight coefficient corresponding to overall performane；Effect score value generation module, for obtaining the weight coefficient of each analysis indexes and each confession in most subordinate's analysis indexes grade The scoring of each analysis indexes in the most subordinate analysis indexes grade corresponding to quotient is answered, respectively analyzes and refers in calculating most subordinate's analysis indexes grade Target effect score value；Assessment result acquisition module, for the effect score value of whole analysis indexes in most subordinate's analysis indexes grade to be added to obtain The final assessment point of each supplier.
- 6. the nonstandard components supplying quotient manufacturing capacity analytical equipment based on analytic hierarchy process (AHP) as claimed in claim 5, feature It is：The weight coefficient generation module includes：Comparator matrix table structure module two-by-two, with analysis indexes grade, creation analysis index is described two-by-two to comparing matrix table step by step Matrix element be in matrix table two analysis indexes corresponding with the matrix element two-by-two compared with obtain after relative importance Relatively important coefficient.
- 7. the nonstandard components supplying quotient manufacturing capacity analytical equipment based on analytic hierarchy process (AHP) as claimed in claim 6, special Sign is：The weight coefficient generation module further comprises：Module is normalized, for by the phase in the sub-goal layer pairwise comparison matrix table and indicator layer pairwise comparison matrix table Significant coefficient is normalized by row；Summation module, for the analysis indexes grade after normalization comparator matrix table and indicator layer pairwise comparison matrix table two-by-two Again by row summation, feature vector is obtained；Weight computation module, for by the total quantity of described eigenvector divided by higher level's analysis indexes, obtaining each analysis indexes grade In each analysis indexes grade analysis indexes corresponding to weight coefficient and each weight coefficient.
- 8. the nonstandard components supplying quotient manufacturing capacity analytical equipment based on analytic hierarchy process (AHP) as claimed in claim 7, special Sign is：The assessment result acquisition module includes：Sorting module, for the final assessment point sequence of each analysis indexes of several suppliers to be obtained supplier's manufacturing capacity Sequence.
- 9. the nonstandard components supplying quotient manufacturing capacity analytical equipment based on analytic hierarchy process (AHP) as claimed in claim 8, special Sign is：The assessment models structure module includes creation analysis index grade and each analysis integrally being required to refer to according to buying industry The analysis indexes of grade are marked, carry out fuzzy evaluation judgement for party in request, the analysis indexes include quality control, technical capability, confession The combination of one or more of goods ability, cost control and flexibility ratio；The personalized customization type assessment models are as desired The specific analysis indexes for requiring parameter creation analysis index grade and each analysis indexes grade of side.
- 10. the nonstandard components supplying quotient manufacturing capacity analytical equipment based on analytic hierarchy process (AHP) as claimed in claim 9, special Sign is：The supplier can be between several new suppliers of party in request, to find the supplier met the requirements；It can also Several new suppliers and several existing suppliers for party in request to improve supplier's inventory, promote party in request's supply chain management Efficiency.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810036788.XA CN108256763A (en) | 2018-01-15 | 2018-01-15 | Nonstandard components supplying quotient manufacturing capacity analysis method and device based on analytic hierarchy process (AHP) |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810036788.XA CN108256763A (en) | 2018-01-15 | 2018-01-15 | Nonstandard components supplying quotient manufacturing capacity analysis method and device based on analytic hierarchy process (AHP) |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108256763A true CN108256763A (en) | 2018-07-06 |
Family
ID=62726553
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810036788.XA Pending CN108256763A (en) | 2018-01-15 | 2018-01-15 | Nonstandard components supplying quotient manufacturing capacity analysis method and device based on analytic hierarchy process (AHP) |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108256763A (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110348788A (en) * | 2019-07-12 | 2019-10-18 | 苏州协鑫新能源运营科技有限公司 | Procurement demand automatic processing method |
| CN110826829A (en) * | 2018-08-13 | 2020-02-21 | 广州凌谷网络科技有限公司 | Intelligent scoring and scheduling method based on big data |
| CN111428182A (en) * | 2020-02-24 | 2020-07-17 | 数字广东网络建设有限公司 | Evaluation index processing method and device, computer equipment and storage medium |
| CN111598660A (en) * | 2020-05-14 | 2020-08-28 | 杭州乐顺科技有限公司 | Computer screening device and method for screening suppliers and storage medium |
| CN111626631A (en) * | 2020-06-03 | 2020-09-04 | 国网浙江省电力有限公司经济技术研究院 | Evaluation method and device for power grid production technical improvement project |
| CN111931291A (en) * | 2020-07-27 | 2020-11-13 | 中国第一汽车股份有限公司 | Noise index decomposition method considering cost |
| CN112749908A (en) * | 2021-01-15 | 2021-05-04 | 上海航天计算机技术研究所 | Supplier reliability analysis system and analysis method |
| CN115657533A (en) * | 2022-10-19 | 2023-01-31 | 扬力集团股份有限公司 | Edge control equipment and control method for press machine |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103413020A (en) * | 2013-06-25 | 2013-11-27 | 武汉理工大学 | Workshop-level manufacturing capability oriented dynamic comprehensive assessment method |
| CN103886168A (en) * | 2012-12-19 | 2014-06-25 | 腾讯科技（深圳）有限公司 | Multi-channel analysis method and device based on analytic hierarchy process |
| CN105654175A (en) * | 2015-12-24 | 2016-06-08 | 北方民族大学 | Part supplier multi-target preferable selection method orienting bearing manufacturing enterprises |
| CN106504015A (en) * | 2016-10-17 | 2017-03-15 | 鞍钢集团矿业有限公司 | A kind of field supplier of enterprise of combination BP neural network recommends method |
| CN107341332A (en) * | 2017-03-10 | 2017-11-10 | 北京理工大学 | A kind of determination method of the evaluation criterion weight of automobile motor drive system |
| CN107563672A (en) * | 2017-09-29 | 2018-01-09 | 云南中烟工业有限责任公司 | A kind of method based on analytic hierarchy process (AHP) structure cigarette primary processing Environmental Evaluation Model |
-
2018
- 2018-01-15 CN CN201810036788.XA patent/CN108256763A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103886168A (en) * | 2012-12-19 | 2014-06-25 | 腾讯科技（深圳）有限公司 | Multi-channel analysis method and device based on analytic hierarchy process |
| CN103413020A (en) * | 2013-06-25 | 2013-11-27 | 武汉理工大学 | Workshop-level manufacturing capability oriented dynamic comprehensive assessment method |
| CN105654175A (en) * | 2015-12-24 | 2016-06-08 | 北方民族大学 | Part supplier multi-target preferable selection method orienting bearing manufacturing enterprises |
| CN106504015A (en) * | 2016-10-17 | 2017-03-15 | 鞍钢集团矿业有限公司 | A kind of field supplier of enterprise of combination BP neural network recommends method |
| CN107341332A (en) * | 2017-03-10 | 2017-11-10 | 北京理工大学 | A kind of determination method of the evaluation criterion weight of automobile motor drive system |
| CN107563672A (en) * | 2017-09-29 | 2018-01-09 | 云南中烟工业有限责任公司 | A kind of method based on analytic hierarchy process (AHP) structure cigarette primary processing Environmental Evaluation Model |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110826829A (en) * | 2018-08-13 | 2020-02-21 | 广州凌谷网络科技有限公司 | Intelligent scoring and scheduling method based on big data |
| CN110348788A (en) * | 2019-07-12 | 2019-10-18 | 苏州协鑫新能源运营科技有限公司 | Procurement demand automatic processing method |
| CN111428182A (en) * | 2020-02-24 | 2020-07-17 | 数字广东网络建设有限公司 | Evaluation index processing method and device, computer equipment and storage medium |
| CN111428182B (en) * | 2020-02-24 | 2023-06-13 | 数字广东网络建设有限公司 | Evaluation index processing method, device, computer equipment and storage medium |
| CN111598660A (en) * | 2020-05-14 | 2020-08-28 | 杭州乐顺科技有限公司 | Computer screening device and method for screening suppliers and storage medium |
| CN111626631A (en) * | 2020-06-03 | 2020-09-04 | 国网浙江省电力有限公司经济技术研究院 | Evaluation method and device for power grid production technical improvement project |
| CN111931291A (en) * | 2020-07-27 | 2020-11-13 | 中国第一汽车股份有限公司 | Noise index decomposition method considering cost |
| CN111931291B (en) * | 2020-07-27 | 2022-10-28 | 中国第一汽车股份有限公司 | Noise index decomposition method considering cost |
| CN112749908A (en) * | 2021-01-15 | 2021-05-04 | 上海航天计算机技术研究所 | Supplier reliability analysis system and analysis method |
| CN115657533A (en) * | 2022-10-19 | 2023-01-31 | 扬力集团股份有限公司 | Edge control equipment and control method for press machine |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108256763A (en) | Nonstandard components supplying quotient manufacturing capacity analysis method and device based on analytic hierarchy process (AHP) | |
| Özcan et al. | Comparative analysis of multi-criteria decision making methodologies and implementation of a warehouse location selection problem | |
| JP6972269B2 (en) | Supplier evaluation equipment and supplier evaluation method | |
| Truong et al. | Simulation based optimization for supply chain configuration design | |
| CN108537623A (en) | Supplier recommends method and system in a kind of e-commerce | |
| Chakraborty et al. | Multi criteria decision making methods for location selection of distribution centers | |
| CN109063976A (en) | Intelligence manufacture capability maturity evaluation method based on Fuzzy AHP | |
| CN106504015A (en) | A kind of field supplier of enterprise of combination BP neural network recommends method | |
| Mousavi et al. | A hierarchical group decision-making approach for new product selection in a fuzzy environment | |
| CN108154277A (en) | Nonstandard Parts Purchasing decision system based on manufacturing capacity and relation chain | |
| CN110826886A (en) | Electric power customer portrait construction method based on clustering algorithm and principal component analysis | |
| CN112860769B (en) | Energy planning data management system | |
| Bulgurcu | Financial performance ranking of automotive industry firms in Turkey: Evidence from entropy weighted technique | |
| CN109345050A (en) | A kind of quantization transaction prediction technique, device and equipment | |
| CN110163486A (en) | A kind of project risk different degree appraisal procedure and system | |
| CN112183920A (en) | Industrial product optimal cost method and device based on analytic hierarchy process | |
| CN107392426A (en) | The evaluation and system of selection of a kind of electricity provider | |
| Oukil et al. | A hybrid multi‐attribute decision‐making procedure for ranking project proposals: A historical data perspective | |
| Vatansever et al. | Integrated usage of fuzzy multi criteria decision making techniques for machine selection problems and an application | |
| CN113763154A (en) | Steel trade supply chain financial risk assessment method based on fuzzy grey evaluation | |
| CN111861679A (en) | Commodity recommendation method based on artificial intelligence | |
| CN114819692A (en) | Business risk analysis method, device, equipment and storage medium | |
| Chaudhary et al. | Comparative analysis of entropy weight method and c5 classifier for predicting employee churn | |
| CN114139065A (en) | Talent screening and recommending method and system based on big data and readable storage medium | |
| CN110837952A (en) | Game theory-based power grid new technology equipment selection method and system |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180706 |