CN116341276A - Scoring method for coating process - Google Patents
Scoring method for coating process Download PDFInfo
- Publication number
- CN116341276A CN116341276A CN202310384211.9A CN202310384211A CN116341276A CN 116341276 A CN116341276 A CN 116341276A CN 202310384211 A CN202310384211 A CN 202310384211A CN 116341276 A CN116341276 A CN 116341276A
- Authority
- CN
- China
- Prior art keywords
- coating
- evaluation
- index
- weight
- coating 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.)
- Pending
Links
- 238000000576 coating method Methods 0.000 title claims abstract description 156
- 238000013077 scoring method Methods 0.000 title claims abstract description 30
- 238000011156 evaluation Methods 0.000 claims abstract description 56
- 239000011159 matrix material Substances 0.000 claims abstract description 34
- 238000000034 method Methods 0.000 claims abstract description 26
- 239000011248 coating agent Substances 0.000 claims description 81
- 238000013210 evaluation model Methods 0.000 claims description 23
- 239000003973 paint Substances 0.000 claims description 20
- 238000007591 painting process Methods 0.000 claims description 13
- 238000010276 construction Methods 0.000 claims description 8
- 238000010422 painting Methods 0.000 claims description 8
- 238000006467 substitution reaction Methods 0.000 claims description 6
- 238000005259 measurement Methods 0.000 claims description 3
- 238000013441 quality evaluation Methods 0.000 claims description 3
- 230000000694 effects Effects 0.000 abstract description 8
- 238000004458 analytical method Methods 0.000 abstract description 5
- 206010063385 Intellectualisation Diseases 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 230000007797 corrosion Effects 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 229910052751 metal Inorganic materials 0.000 description 1
- 239000013535 sea water Substances 0.000 description 1
- 238000005507 spraying Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression 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
- 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
-
- 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
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Data Mining & Analysis (AREA)
- Human Resources & Organizations (AREA)
- Mathematical Physics (AREA)
- Pure & Applied Mathematics (AREA)
- Computational Mathematics (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Algebra (AREA)
- Databases & Information Systems (AREA)
- Strategic Management (AREA)
- Software Systems (AREA)
- Operations Research (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Computer Hardware Design (AREA)
- Marketing (AREA)
- Tourism & Hospitality (AREA)
- Quality & Reliability (AREA)
- Geometry (AREA)
- Evolutionary Computation (AREA)
- General Business, Economics & Management (AREA)
- Game Theory and Decision Science (AREA)
- Computing Systems (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Probability & Statistics with Applications (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a coating process scoring method, which comprises the following steps: selecting and determining an evaluation index of the coating process; constructing a hierarchical analysis model according to the evaluation index; constructing a judgment matrix by the analytic hierarchy process model; calculating index weight by the judgment matrix; and calculating according to the index weight to obtain the comprehensive coating process evaluation score. By adopting the grading method, each important index of the coating process is effectively analyzed and judged, the weight coefficient of each index is calculated by establishing a hierarchical analysis model, the evaluation score of each index of the coating process and the comprehensive evaluation score of the coating process are obtained by calculating according to the weight coefficient, and finally, the coating process with the optimal effect is determined and recommended to a decision maker.
Description
Technical Field
The invention relates to a scoring method for a coating process.
Background
Before the ship is launched, the surface of the ship is coated, and the ship can be protected from corrosion by spraying and protecting coating due to the fact that the seawater has certain metal corrosiveness.
In the existing ship coating process, the quality of the coating process needs to be considered in various aspects, such as the amount of paint, the man-hours spent on coating, the quality of the coating itself, and the like. The amount of the paint may be affected by various factors such as the environment at the time of painting, the structure of the ship, the roughness of the surface of the ship, the paint performance, the coating mode, the construction skill, etc.; the working hours spent in coating can also be changed according to the size, the structure and the coating difficulty of the ship; the quality of the coating is often judged according to the thickness and uniformity of the paint film after coating. It can be seen that the coating process of the ship involves a very large number of influencing factors, but in the prior art, no good scoring method for the coating process can cover the factors of coating amount, coating man-hour and coating quality.
Disclosure of Invention
The invention aims to overcome the defect that the coating process of a ship cannot be comprehensively evaluated in the prior art, and provides a scoring method for the coating process.
The invention solves the technical problems by the following technical scheme:
a painting process scoring method, the painting process scoring method comprising the steps of:
s1, selecting and determining an evaluation index of the coating process;
s2, constructing an analytic hierarchy process model according to the evaluation index;
s3, constructing a judgment matrix by the analytic hierarchy process model;
s4, calculating index weight by the judgment matrix;
and S5, calculating according to the index weight to obtain an integrated coating process evaluation score.
According to the scheme, the important indexes of the coating process are effectively analyzed and judged by the scoring method, the weight coefficient of each index is calculated by establishing the analytic hierarchy model, the evaluation score of each index of the coating process and the comprehensive evaluation score of the coating process are obtained by calculating according to the weight coefficient, and finally, the coating process with the optimal effect is determined and recommended to a decision maker.
Preferably, step S3.1 is included between steps S3 and S4, and consistency check is performed according to the constructed judgment matrix, so as to calculate a consistency index CI, a consistency ratio CR, and judge whether the consistency check is passed.
Preferably, step S3.2 is provided after step S3.1, and if the consistency ratio CR is less than 0.1, the consistency check is passed, and S4 is executed, and if the consistency ratio CR is greater than 0.1, the consistency check is not passed, and S3 is executed and the judgment matrix is reconstructed.
In the scheme, the consistency test is carried out on the constructed judgment matrix, so that the accuracy of the established judgment matrix is effectively determined, the authenticity and consistency of a calculation result are further ensured, and the practicability and the reference value of the scoring method are effectively improved.
Preferably, in S2, the analytic hierarchy process model includes a target layer, a criterion layer and a process layer, where the target layer is a target of a coating process achieved by applying the method, the criterion layer is an index included in a coating process target of the target layer, and the process layer is a plurality of coating processes used.
Preferably, the criterion layer includes painting man-hour, coating quality and painting amount.
In the scheme, three indexes of coating time, coating quality and coating consumption of various coating processes are analyzed to judge the matching effect of the three indexes with an ideal target, so that various coating processes are scored and selected, and the scoring method is more comprehensive and objective and has higher reference value.
Preferably, in S3, according to the analytic hierarchy process model constructed in S2, the relative importance between each element of the criterion layer is determined, the determination matrix a is constructed, and the weight coefficient of each element is obtained by calculating according to the determination matrix a, where the determination matrix a is as follows:
wherein a is 12 Representing the importance of element 1 and element 2 relative to the target.
Preferably, in S4, the method further includes calculating a tag weight, where the tag weight and the index weight calculate an actual weight of each evaluation index, and the tag weight and the index weight calculate the actual weight through a fuzzy calculation formula, where the fuzzy calculation formula is:
wherein λ represents an actual weight; w is an index weight; w (W) T Is the label weight;
and (5) representing the fuzzy operator, and adopting a weighted average model as an operator model.
In the scheme, the label weight is introduced into the weight calculation, and the label weight of the user is integrated with the weight calculated by the judgment matrix to obtain the final actual weight, so that the scoring method meets the unification of objective rules of process designers and evaluation targets from the actual situation, the reliability of the weight is objectively, reasonably, truly and effectively reflected by the calculation result, and the rationality and the intellectualization of the coating process are reflected.
Preferably, S5 further includes substitution of coating process parameters, construction of a multi-objective evaluation model of the coating process, and construction of a comprehensive evaluation model, wherein substitution of the coating process parameters indicates that the weights calculated in S4 are brought into the coating objective function, and the multi-objective evaluation model is constructed, and the comprehensive evaluation model is constructed by the multi-objective evaluation model.
Preferably, the coating objective function includes a coating quality objective function Y H Target function Y of paint dosage V And a coating man-hour objective function Y t Calculating the coating objective function to obtain quality evaluation, consumption evaluation and working hours evaluation of the coating, and establishing the multi-objective evaluation model;
wherein the coating quality objective function Y H The following are provided:
wherein T is 0 For rated dry film thickness, T max,i And T min,i The maximum and minimum dry film thickness in region i, respectively, a being the number of measurement regions,
s is the coating area, i is the area number, k T,i Is a weighting coefficient associated with the region;
coating quantity target function Y V The following are provided:
in which Q act For actual paint usage, Q rat The paint is rated for paint consumption;
coating man-hour objective function Y t The following are provided:
wherein C is act C is the actual painting working hour rat The coating time is the rated coating time.
Preferably, a multi-target comprehensive evaluation function Y is obtained according to the multi-target evaluation model eval Establishing a comprehensive evaluation model, calculating a comprehensive evaluation score of the coating process, and calculating a multi-objective comprehensive evaluation function Y eval The following are provided:
wherein Y is H 、Y V And Y T Respectively the coating quality objective function Y H Target function Y of paint dosage V And a coating man-hour objective function Y t ，λ H 、λ V And lambda (lambda) T The factors of influence are related to the coating quality, the coating amount and the coating work, respectively.
Preferably, after the scoring data is obtained by calculating the steps of each coating process, sorting is carried out according to the scores of the comprehensive evaluation scores, the coating process with the highest comprehensive evaluation score is selected, and a coating process table is manufactured for the coating process.
The invention has the positive progress effects that:
according to the evaluation method, all important indexes of the coating process are effectively analyzed and judged, a hierarchical analysis model is established, the weight coefficient of each index is calculated, the evaluation score of each index of the coating process and the comprehensive evaluation score of the coating process are obtained through calculation according to the weight coefficient, finally, the coating process with the optimal effect is determined and recommended to a decision maker, and the evaluation method is objective and reasonable and comprehensively considers all indexes in the ship coating process, so that the evaluation is true and reliable.
Drawings
Fig. 1 is a flowchart 1 of the scoring method of the painting process in this embodiment.
Fig. 2 is a flowchart of the scoring method of the painting process in this embodiment 2.
Fig. 3 is a schematic diagram of the analytic hierarchy model constructed in this embodiment.
Detailed Description
The invention is further illustrated by means of examples which follow, without thereby restricting the scope of the invention thereto.
As shown in fig. 1 to 3, the present invention discloses a painting process scoring method, which includes the steps of:
s1, selecting and determining an evaluation index of a coating process;
s2, constructing an analytic hierarchy process model according to the evaluation index;
s3, constructing a judgment matrix by the analytic hierarchy process model;
s4, calculating index weight by a judgment matrix;
and S5, calculating according to the index weight to obtain the comprehensive coating process evaluation score.
In this embodiment, the above scoring method effectively analyzes and judges each important index of the coating process, establishes a analytic hierarchy process model, calculates the weight coefficient of each index, calculates the evaluation score of each index of the coating process according to the weight coefficient, and the comprehensive evaluation score of the coating process, and finally determines a coating process with optimal effect to recommend to a decision maker.
Specifically, as shown in fig. 2, step S3.1 is included between steps S3 and S4, and consistency check is performed according to the constructed judgment matrix, a consistency index CI is calculated, a consistency ratio CR is calculated, and whether the consistency check is passed or not is judged.
Specifically, step S3.2 is provided after step S3.1, and if the consistency ratio CR is smaller than 0.1, the consistency check is passed, and S4 is executed, and if the consistency ratio CR is larger than 0.1, the consistency check is not passed, and S3 is executed and the judgment matrix is reconstructed.
The consistency test is carried out on the constructed judgment matrix, so that the accuracy of the established judgment matrix is effectively determined, the authenticity and consistency of a calculation result are further ensured, and the practicability and the reference value of the scoring method are effectively improved.
Specifically, three evaluation indexes of coating time, coating quality and coating dosage are selected in this embodiment, and a hierarchical analysis model shown in fig. 3 is established according to the three evaluation indexes, where the hierarchical analysis model includes a target layer, a criterion layer and a process layer, the target layer represents a target effect of a coating process to be achieved in an ideal state, the criterion layer represents indexes included in a coating process target of the target layer, that is, three evaluation indexes of coating time, coating quality and coating dosage, and the process layer is a plurality of coating processes adopted.
In the model, three indexes of coating time, coating quality and coating consumption of various coating processes are analyzed to judge the coincidence effect of the three indexes with an ideal target, so that various coating processes are scored and selected, and the scoring method is more comprehensive and objective and has higher reference value.
Specifically, in S3, according to the analytic hierarchy process model constructed in S2, the relative importance between any two elements is determined by comparing the elements of the criterion layer, and according to three evaluation indexes of the ship coating process, an index set is formed, denoted as d= (D) 1 ,D 2 ,D 3 ) And constructing the index set into a third-order judgment matrix A, and calculating the weight coefficient of each element according to the judgment matrix A, wherein the judgment matrix A is as follows:
wherein a is 12 Representing the importance of element 1 and element 2 relative to the target.
In this embodiment, an expert fills out the element values of the judgment matrix according to experience, and integrates the calculation results into table 1 as follows:
table 1 judgment matrix table
As can be seen from table 1, the index weights of the painting man-hour, the coating quality and the paint amount calculated from the judgment matrix were 0.2828, 0.3738 and 0.3434, respectively.
Specifically, in S4, the method further includes calculating a tag weight, where the tag weight and an index weight obtain actual weights of the evaluation indexes, and the tag weight and the index weight calculate the actual weights through a fuzzy calculation formula, where the fuzzy calculation formula is:
wherein λ represents an actual weight; w is an index weight; w (W) T Is the label weight; the degree represents a fuzzy operator, and a weighted average model is adopted as an operator model.
In this embodiment, taking an H1127/7 type ship as an example, the tag weight W is selected by a craftsman T As shown in table 2, the following is:
table 2 tag weights selected by the craftsman
Calculating the index weight calculated in the table 1 and the label weight selected by the process staff in the table 2 according to the fuzzy formula to obtain the actual weight of each evaluation target in the whole coating process evaluation target system, wherein the actual weights are respectively as follows:
λ T ＝0.09898,λ H ＝0.11214,λ V ＝0.12019
wherein lambda is T Lambda is the actual weight of the painting man-hour H Lambda is the actual weight of the coating quality V The actual weight is the coating amount.
In the embodiment, the label weight is introduced into the weight calculation, and the label weight of the user is integrated with the weight calculated by the judgment matrix to obtain the final actual weight, so that the scoring method meets the unification of objective rules of process designers and evaluation targets from the actual condition, the reliability of the weight is objectively, reasonably, truly and effectively reflected by the calculation result, and the rationality and the intellectualization of the coating process are reflected.
Specifically, S5 further includes substitution of coating process parameters, construction of a multi-objective evaluation model of the coating process, and construction of a comprehensive evaluation model, wherein substitution of coating process parameters means that the weights calculated in S4 are brought into the coating objective function, and the multi-objective evaluation model is established, and the comprehensive evaluation model is constructed by the multi-objective evaluation model.
Specifically, the coating objective function includes a coating quality objective function Y H Target function Y of paint dosage V And a coating man-hour objective function Y t Calculating a coating objective function to obtain quality evaluation, consumption evaluation and working hours evaluation of the coating, and establishing a multi-objective evaluation model;
wherein the coating quality objective function Y H The following are provided:
wherein T is 0 For rated dry film thickness, T max,i And T min,i The maximum and minimum dry film thickness in region i, respectively, a being the number of measurement regions,
s is the coating area, i is the area number, k T,i Is a weighting coefficient associated with the region;
coating quantity target function Y V The following are provided:
in which Q act For actual paint usage, Q rat The paint is rated for paint consumption;
coating man-hour objective function Y t The following are provided:
wherein C is act C is the actual painting working hour rat The coating time is the rated coating time.
Specifically, according to the multi-objective evaluation model, a multi-objective comprehensive evaluation function Y is obtained eval Establishing a comprehensive evaluation model, calculating a comprehensive evaluation score of the coating process, and calculating a multi-objective comprehensive evaluation function Y eval The following are provided:
wherein Y is H 、Y V And Y T Respectively the coating quality objective function Y H Target function Y of paint dosage V And a coating man-hour objective function Y t ，λ H 、λ V And lambda (lambda) T The actual weights of the coating quality, the coating amount and the coating man-hour are respectively.
Lambda calculated above H 、λ V And lambda (lambda) T Respectively carrying into multi-objective comprehensive evaluation function Y eval After the scoring data is obtained by the calculation of the steps, the scoring data are sorted according to the score of the comprehensive evaluation score, and an evaluation matrix list is produced, as shown in table 3:
table 3 evaluation matrix list
According to table 3, the coating process with the highest comprehensive evaluation score was selected, and a coating process table was prepared for it, and this coating process table was recommended to the decision maker as shown in table 4:
table 4 coating process table
While specific embodiments of the invention have been described above, it will be appreciated by those skilled in the art that this is by way of example only, and the scope of the invention is defined by the appended claims. Various changes and modifications to these embodiments may be made by those skilled in the art without departing from the principles and spirit of the invention, but such changes and modifications fall within the scope of the invention.
Claims (10)
1. A painting process scoring method, characterized in that the painting process scoring method comprises the steps of:
s1, selecting and determining an evaluation index of the coating process;
s2, constructing an analytic hierarchy process model according to the evaluation index;
s3, constructing a judgment matrix by the analytic hierarchy process model;
s4, calculating index weight by the judgment matrix;
and S5, calculating according to the index weight to obtain an integrated coating process evaluation score.
2. The painting process scoring method according to claim 1, wherein step S3.1 is included between steps S3 and S4, and consistency check is performed according to the constructed judgment matrix, a consistency index CI is calculated, a consistency ratio CR is calculated, and whether or not the consistency check is passed is judged.
3. The coating process scoring method according to claim 2, wherein step S3.2 is provided after step S3.1, and if the consistency ratio CR is less than 0.1, the consistency check is passed, and S4 is performed, and if the consistency ratio CR is greater than 0.1, the consistency check is not passed, and S3 is performed and the judgment matrix is reconstructed.
4. The coating process scoring method according to claim 1, wherein in S2, the analytic hierarchy model includes a target layer, a criterion layer and a process layer, the target layer is a target of a coating process achieved by applying the method, the criterion layer is an index included in achieving a coating process target of the target layer, and the process layer is a plurality of coating processes adopted.
5. The coating process scoring method of claim 4, wherein the guideline layer comprises a coating man-hour, a coating quality, and a coating amount.
6. The coating process scoring method according to claim 4, wherein in S3, the relative importance between any two elements is determined according to the analytic hierarchy process model constructed in S2, the determination matrix a is constructed, the weight coefficient of each element is calculated according to the determination matrix, and the determination matrix a is as follows:
wherein a is 12 Representing the importance of element 1 and element 2 relative to the target.
7. The painting process scoring method according to claim 1, further comprising a tag weight, wherein the tag weight and the index weight are calculated to obtain an actual weight of each evaluation index, and the tag weight and the index weight are calculated by a fuzzy calculation formula, wherein the fuzzy calculation formula is as follows:
wherein λ represents an actual weight; w is an index weight; w (W) T Is the label weight；
And (5) representing the fuzzy operator, and adopting a weighted average model as an operator model.
8. The painting process scoring method according to claim 1, wherein S5 further comprises substitution of painting process parameters, construction of a painting process multi-objective evaluation model, and construction of a comprehensive evaluation model, the substitution of painting process parameters representing that the weights calculated in S4 are brought into the coating objective function, and construction of a multi-objective evaluation model, from which the comprehensive evaluation model is constructed.
9. The coating process scoring method of claim 8, wherein the coating objective function comprises a coating quality objective function Y H Target function Y of paint dosage V And a coating man-hour objective function Y t Calculating the coating objective function to obtain quality evaluation, consumption evaluation and working hours evaluation of the coating, and establishing the multi-objective evaluation model;
wherein the coating quality objective function Y H The following are provided:
wherein T is 0 For rated dry film thickness, T max,i And T min,i The maximum and minimum dry film thickness in region i, respectively, a being the number of measurement regions,
s is the coating area, i is the area number, k T,i Is a weighting coefficient associated with the region;
coating quantity target function Y V The following are provided:
in which Q act For actual paint usage, Q rat The paint is rated for paint consumption;
coating man-hour objective function Y t The following are provided:
wherein C is act C is the actual painting working hour rat The coating time is the rated coating time.
10. The coating process scoring method of claim 9, wherein a multi-objective comprehensive evaluation function Y is obtained from the multi-objective evaluation model eval Establishing a comprehensive evaluation model, calculating a comprehensive evaluation score of the coating process, and calculating a multi-objective comprehensive evaluation function Y eval The following are provided:
wherein Y is H 、Y V And Y T Respectively the coating quality objective function Y H Target function Y of paint dosage V And a coating man-hour objective function Y t ，λ H 、λ V And lambda (lambda) T The factors of influence are related to the coating quality, the coating amount and the coating work, respectively.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310384211.9A CN116341276A (en) | 2023-04-12 | 2023-04-12 | Scoring method for coating process |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310384211.9A CN116341276A (en) | 2023-04-12 | 2023-04-12 | Scoring method for coating process |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116341276A true CN116341276A (en) | 2023-06-27 |
Family
ID=86893006
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310384211.9A Pending CN116341276A (en) | 2023-04-12 | 2023-04-12 | Scoring method for coating process |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116341276A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116862160A (en) * | 2023-06-29 | 2023-10-10 | 盐城工学院 | Multi-target balance optimization method for automobile coating production line |
-
2023
- 2023-04-12 CN CN202310384211.9A patent/CN116341276A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116862160A (en) * | 2023-06-29 | 2023-10-10 | 盐城工学院 | Multi-target balance optimization method for automobile coating production line |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111950918B (en) | Market risk assessment method based on power transaction data | |
| CN116341276A (en) | Scoring method for coating process | |
| CN108256761A (en) | Overhead weapon station grey fuzzy comprehensive evaluation method | |
| Frankel | Hierarchical logic in shipping policy and decision-making | |
| Anton et al. | Measuring the effectiveness of competition in defense procurement: A survey of the empirical literature | |
| CN113408869A (en) | Power distribution network construction target risk assessment method | |
| CN112884359A (en) | Electric power spot market risk assessment method | |
| CN111626844A (en) | Enterprise credit assessment method and device based on big data analysis | |
| CN114997514A (en) | Evaluation and prediction method for development degree of rammed earth site crack diseases | |
| CN111047197A (en) | Strategic attack and defense decision assessment method and device | |
| CN113222261A (en) | Scientific and invasive board enterprise valuation system based on gray prediction and BP-ARIMA | |
| Shafei et al. | Predicting and Studying the Effect of Uncertainty in the Real Exchange Rate on the Agricultural Department Imports of Iran | |
| CN110135085B (en) | Fatigue crack evaluation method based on adaptive kernel density estimation auxiliary particle filter | |
| CN116502804A (en) | Maintenance guarantee point site selection method | |
| Melendez et al. | Tourism demand modeling and forecasting for El Salvador | |
| CN114021905A (en) | Credit risk evaluation method for small and medium-sized enterprises | |
| CN108053266A (en) | A kind of patent value predictor method and device | |
| CN114358612A (en) | Subjective evaluation method for automobile | |
| Naghibi et al. | Explanation of effective components in the structure of world class manufacturing in the automotive industry | |
| CN109327476B (en) | Method and system for evaluating risk of Web attack on information system | |
| Yin et al. | Corrosion assessment: Data mining for quantifying associations between indoor accelerated and outdoor natural tests | |
| CN110673084A (en) | State evaluation method and device for electric energy metering device and readable storage medium | |
| CN117710008B (en) | Ecological product sales information management system suitable for karst region | |
| CN110879723B (en) | Objective evaluation method and device for software service value based on Pareto optimal set | |
| CN113537684B (en) | Overseas refining chemical engineering risk management control method under multi-target coupling constraint |
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 |