CN107133727A - Dimensionality optimization method is assessed based on the failure effect for differentiating force coefficient - Google Patents
Dimensionality optimization method is assessed based on the failure effect for differentiating force coefficient Download PDFInfo
- Publication number
- CN107133727A CN107133727A CN201710267849.9A CN201710267849A CN107133727A CN 107133727 A CN107133727 A CN 107133727A CN 201710267849 A CN201710267849 A CN 201710267849A CN 107133727 A CN107133727 A CN 107133727A
- Authority
- CN
- China
- Prior art keywords
- mrow
- msub
- dimension
- mtd
- munderover
- 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
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
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- 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
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Operations Research (AREA)
- Marketing (AREA)
- Game Theory and Decision Science (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a kind of based on the failure effect assessment Dimensionality optimization method for differentiating force coefficient, aspect according to involved by influenceing process failure and the corresponding relation between the type of business accountability, according to Boundary of Property Rights is theoretical, Perceived Risk is theoretical and manufactures maturity theory, the manufacturing process failure severity assessment dimension system with systemic theoretical foundation and completeness is built.Then, the taste coefficient formulas available for fuzzy risk evaluating is created.Finally, minimized with dimension number and system information content maximum turns to target, using requirement of the PCA to system completeness as constraints, establish the multiple target mathematic optimal model that data are assessed based on each dimension weight and each dimension, dimension is chosen and optimized, the equalization point for seeking most preferably between the completeness and terseness of dimension system.
Description
Technical field
The present invention relates to technological evaluation optimisation technique, concretely relate to assess based on the failure effect for differentiating force coefficient
Dimensionality optimization method.
Background technology
PFMEA (Process Failure Mode and Effects Analysis, process failure pattern and influence point
Analysis) it is a kind of it is main used by manufacture and Assembly Engineers, it has systematization and perspective technical Analysis method, causes
Power is likely to occur potential PFM (Process Failure Mode, process failure pattern) in being identified in the product manufacturing stage,
Assess the influence degree caused by failure mode.And according to the risk class order of each pattern, rational allocation limited resources are taken
Corresponding process modification and precautionary measures, to avoid and reduce failure risk, minimize business accountability and fault, avoid as far as possible
Reparation is lost with reducing.PFMEA originates from U.S. spaceflight Aerobiz, and is gradually opened up to industries such as machinery, automobile, Medical Devices
Exhibition so that the reliability of these industry products is greatly improved.
In actual PFMEA projects, generally from severity, occurrence frequency, detection difficulty in terms of these three to multiple works
Skill failure mode carries out risk assessment, to determine the order of priority of risk.Wherein, the assessment of severity is mostly important.Work as technique
When the severity of failure mode is cited as 9,10 grade, then it need not pay close attention to and situation is assessed of both other, directly by the pattern
It is classified as critical process failure pattern.However, the assessment of severity needs the dimension considered a lot.Geng Xiuli[1]From safety
Property, reliability, economy this three aspect go assess severity；Braglia M[2]From safety, quality, maintenance cost, average repairing
This four aspects of time go to assess；Wang Shaoyin[3]Then from product function realization, Product Usability, the personal safety of user, repair
Scrapping after the expense that fails again, the operation ease of user, the difficulty for repairing failure, ambient influnence, public safety, failure
This nine aspects of cost go to assess；The studies above personnel are being established when severity assesses dimension system with certain incompleteness
And repeatability, dimension, which is chosen, lacks the scientific theory foundation of systematization.In addition, dimension is excessive, although ensure that the complete of system,
But the workload of assessment experts can be caused to increase, PFMEA execution efficiencys decline；Dimension is very few, although expert can be made to concentrate one's energy
It is estimated in limited dimension, the problem of but triggering inconsiderate, final result is occurred deviation.Therefore, how section
Ground builds severity and assesses dimension system, how to be found most between the terseness of the completeness of dimension and assessment dimension is assessed
Good equalization point, is current urgent problem to be solved, is also the follow-up basis for carrying out severity evaluation studies.
The content of the invention
To solve above-mentioned problem, Dimensionality optimization method is assessed it is an object of the invention to provide a kind of failure effect, is built
Manufacturing process failure severity with systemic theoretical foundation and completeness assesses dimension system, creates and can be used for fuzzy risk
The taste coefficient formulas of assessment, is minimized with dimension number and system information content maximum turns to target, with principal component
Requirement of the analytic approach to system completeness is constraints, sets up the multiple target that data are assessed based on each dimension weight and each dimension
Mathematic optimal model, chooses to dimension and optimizes, the balance for seeking most preferably between the completeness and terseness of dimension system
Point.
The present invention realizes above-mentioned purpose using following technical scheme.Dimension is assessed based on the failure effect for differentiating force coefficient
Optimization method, it is characterised in that its step is as follows：
1) corresponding relation between aspect and the type of business accountability according to involved by influenceing process failure, according to property right
Bounding theory, Perceived Risk are theoretical and manufacture maturity theory, build the manufacture work with systemic theoretical foundation and completeness
Skill failure severity assesses dimension system；
2) each information content for differentiating force coefficient and dimension system for assessing dimension is calculated；
1 is defined, if expert is assessed under dimension at m-th, to PFM1,…,PFMi,…,PFMNCommon N number of process failure mould
Formula carries out severity assessment, obtains Am1,…,Ami,…,AmNN number of assessment data, then N number of to assess the distance between data number altogether
ForThe discriminating force coefficient of m-th of assessment dimension may be defined as the average value of normalized cumulant, specific as follows：
In formula：νmIt is the discriminating force coefficient of m-th of assessment dimension；HE(Ami,Amj) it is assessment number under m-th of assessment dimension
According to AmiWith AmjBetween broad sense Hausdorff distance；
2 are defined, the information content of dimension system characterizes discrimination of the system to each process failure pattern severity,
Show the difference degree of each process failure pattern severity, the calculation formula of the information content of dimension system is as follows：
3) each weight for assessing dimension is calculated using analytic hierarchy process (AHP)；
4) the complete rate of counting system, specific as follows：
In formula：wmIt is the weight of m-th of assessment dimension；M is the dimension total number for assessing dimension system；
5) minimized with dimension number and system information content maximum turns to target, it is complete to system with PCA
Property requirement be constraints, set up the multiple target mathematic optimal model that data are assessed based on each dimension weight and each dimension, tool
Body is as follows：
In formula：vmIt is the discriminating force coefficient of m-th of assessment dimension, can be calculated and obtained by assessment data；wmIt is by level point
The weight for m-th of assessment dimension that analysis method is determined；M is the dimension total number of primary election system；dmIt is 0-1 variables, when value is 0,
Represent to delete m-th of assessment dimension, when value is 1, represent to retain m-th of assessment dimension.
First, influenceed according to process failure between involved aspect and the type of business accountability corresponding closes the present invention
System, according to Boundary of Property Rights is theoretical, Perceived Risk is theoretical and manufactures maturity theory, constructing has systemic theoretical foundation and complete
The manufacturing process failure severity of standby property assesses dimension system.Then, the taste system available for fuzzy risk evaluating is created
Number calculation formula.Finally, minimized with dimension number and system information content maximum turns to target, with PCA to body
The requirement for being completeness is constraints, establishes the multiple target mathematical optimization that data are assessed based on each dimension weight and each dimension
Model, chooses to dimension and optimizes, the equalization point for seeking most preferably between the completeness and terseness of dimension system.
Existing problems are chosen instant invention overcomes Traditional measurements dimension, with advantages below：
1) the assessment dimension system construction based on business accountability type, not only theoretically ensure that and assesses dimension system
Completeness, and PFMEA current demand and significance are highlighted, help to lift the responsibility consciousness of appraiser.
2) brand-new taste coefficient formulas is constructed.The discriminating force coefficient proposed can not only be applied to traditional
Real-valued assesses data, also can be suitably used for assessing data in the widely used fuzzy type of assessment and decision domain.
3) to realize that dimension number is minimized and system information content is maximized, the mathematical optimization mould of multiple target is constructed
Type.The Optimized model synthetically considers that each dimension weighted data assesses data with each dimension, using mathematic optimal model in dimension
The screening strategy for seeking most preferably between the completeness and terseness of system.
Dimension chooses the theoretical foundation with systematization, so that the completeness of dimension system is ensure that, meanwhile, for fuzzy
Risk assessment, creatively constructs brand-new taste coefficient formulas, to calculate the information content of dimension system.
Brief description of the drawings
Fig. 1 is the structure principle of manufacturing process failure severity assessment dimension system in the present invention.
Embodiment
Below in conjunction with drawings and examples, the invention will be further described.Referring to Fig. 1, based on the failure for differentiating force coefficient
Impact evaluation Dimensionality optimization method, implementation step is：
(1) corresponding relation between aspect and the type of business accountability according to involved by influenceing process failure, according to production
Bounding theory, Perceived Risk theory and manufacture maturity theory are weighed, the system with systemic theoretical foundation and completeness is constructed
Make process failure severity and assess dimension system, be specifically shown in Fig. 1, table 1, table 2 and table 3；
Table 1 assesses dimension X towards the severity of end user1
The severity of table 2 towards product manufacturing management activity assesses dimension X2
The severity of the Government decree regulation of table 3 assesses dimension X3
| Assess dimension | Definition |
| The safe X of end user3,1 | Purchased product is to the actual bodily harm degree caused by user or neighbour |
| The safe X of manufacturer3,2 | Process failure causes the extent of injury to manufacturer |
| Environment X3,3 | Process failure causes the extent of injury to environment |
According to repeated dimension combination principle, using artificial scalping mode, 18 dimensions are down to 15 dimensions.Above-mentioned dimension
Degree system is applied to all manufacturing process.It can be minimized with dimension number according to some typical technique cases and information contain
Amount maximum turns to target, and the requirement of system completeness is implemented into one for constraints to this 15 dimensions with PCA
The sieve of step subtracts.
(2) each discriminating force coefficient for assessing dimension is calculated.Now using aircraft combined heat radiator and turbine mounting process as
Example, the further sieve for carrying out data analysis and dimension subtracts, and last optimum results can be applied to other other similar technique shadows
Ring in analysis.The process failure pattern that aircraft combined heat radiator and turbine flow of installation are included is shown in Table 4, Zhuan Jiaping
The form of filling in for estimating opinion is shown in Table 5, and expert assesses data and is shown in Table 6 and table 7.
The aircraft of table 4 combines the process failure pattern of air radiator and turbine flow of installation
The general of the expert's comments of table 5 fills in form
The expert's comments and discriminating force coefficient (assessing dimension D1~D8) of each dimension of table 6
The expert's comments and discriminating force coefficient (assessing dimension D9~D15) of each dimension of table 7
(3) application level analytic approach calculates each dimension weight, concrete outcome such as table 8；
Table 8 respectively assesses the weight of dimension
(4) minimized with dimension number and system information content maximum turns to target, it is complete to system with PCA
The requirement of standby property is constraints, establishes the multiple target mathematical optimization mould that data are assessed based on each dimension weight and each dimension
The complete rate and information content of system after type, and calculation optimization, concrete outcome are as shown in table 9：
The optimum results of the dimension system of table 9
Bibliography：
[1] fault modes and effect analysis methods of risk assessment [J] meters of the peaceful of Geng Xiuli, Chu Xue based on the failure chain of causation
Calculation machine integrated manufacturing system, 2009,15 (12):2473-2480.
[2]Braglia M,Fantoni G,Frosolini M.The house of reliability[J]
.International Journal of Quality&Reliability Management,2007,24(4):420-440.
[3] Wang Shao prints publishing house of failure mode and effect analysis (FMEA)s (FMEA) [M] Zhongshan University, 2003.
Claims (1)
1. Dimensionality optimization method is assessed based on the failure effect for differentiating force coefficient, it is characterised in that its step is as follows：
1) corresponding relation between aspect and the type of business accountability according to involved by influenceing process failure, according to Boundary of Property Rights
Theoretical, Perceived Risk is theoretical and manufactures maturity theory, builds the manufacturing process with systemic theoretical foundation and completeness and loses
Imitate severity and assess dimension system；
2) each information content for differentiating force coefficient and dimension system for assessing dimension is calculated；
1 is defined, if expert is assessed under dimension at m-th, to PFM1,…,PFMi,…,PFMNN number of process failure pattern is entered altogether
Row severity is assessed, and obtains Am1,…,Ami,…,AmNN number of assessment data are total to, then the distance between N number of assessment data number isThe discriminating force coefficient of m-th of assessment dimension may be defined as the average value of normalized cumulant, specific as follows：
<mrow>
<msub>
<mi>v</mi>
<mi>m</mi>
</msub>
<mo>=</mo>
<mfrac>
<mn>2</mn>
<mrow>
<mi>N</mi>
<mrow>
<mo>(</mo>
<mi>N</mi>
<mo>-</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mrow>
</mfrac>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>j</mi>
<mo>=</mo>
<mi>i</mi>
<mo>+</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<mfrac>
<mrow>
<msub>
<mi>H</mi>
<mi>E</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>A</mi>
<mrow>
<mi>m</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>,</mo>
<msub>
<mi>A</mi>
<mrow>
<mi>m</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mi>m</mi>
<mi>i</mi>
<mi>n</mi>
<mo>{</mo>
<msub>
<mi>H</mi>
<mi>E</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>A</mi>
<mrow>
<mi>m</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>,</mo>
<msub>
<mi>A</mi>
<mrow>
<mi>m</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>}</mo>
</mrow>
<mrow>
<mi>max</mi>
<mo>{</mo>
<msub>
<mi>H</mi>
<mi>E</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>A</mi>
<mrow>
<mi>m</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>,</mo>
<msub>
<mi>A</mi>
<mrow>
<mi>m</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>}</mo>
<mo>-</mo>
<mi>m</mi>
<mi>i</mi>
<mi>n</mi>
<mo>{</mo>
<msub>
<mi>H</mi>
<mi>E</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>A</mi>
<mrow>
<mi>m</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>,</mo>
<msub>
<mi>A</mi>
<mrow>
<mi>m</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>}</mo>
</mrow>
</mfrac>
<mo>;</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula：νmIt is the discriminating force coefficient of m-th of assessment dimension；HE(Ami,Amj) it is assessment data A under m-th of assessment dimensionmi
With AmjBetween broad sense Hausdorff distance；
2 are defined, the information content of dimension system characterizes discrimination of the system to each process failure pattern severity, shows
The difference degree of each process failure pattern severity, the calculation formula of the information content of dimension system is as follows：
<mrow>
<mi>I</mi>
<mi>n</mi>
<mi>f</mi>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>Q</mi>
</munderover>
<msub>
<mi>v</mi>
<mi>m</mi>
</msub>
<mo>;</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>2</mn>
<mo>)</mo>
</mrow>
</mrow>
3) each weight for assessing dimension is calculated using analytic hierarchy process (AHP)；
4) the complete rate of counting system, specific as follows：
<mrow>
<mi>p</mi>
<mi>e</mi>
<mi>r</mi>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>M</mi>
</munderover>
<msub>
<mi>w</mi>
<mi>m</mi>
</msub>
<mo>;</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula：wmIt is the weight of m-th of assessment dimension；M is the dimension total number for assessing dimension system；
5) minimized with dimension number and system information content maximum turns to target, with PCA to system completeness
It is required that being constraints, the multiple target mathematic optimal model that data are assessed based on each dimension weight and each dimension is set up, specifically such as
Under：
<mrow>
<mtable>
<mtr>
<mtd>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mi>min</mi>
</mtd>
<mtd>
<mrow>
<msub>
<mi>y</mi>
<mn>1</mn>
</msub>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>M</mi>
</munderover>
<msub>
<mi>d</mi>
<mi>m</mi>
</msub>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mi>max</mi>
</mtd>
<mtd>
<mrow>
<msub>
<mi>y</mi>
<mn>2</mn>
</msub>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>M</mi>
</munderover>
<msub>
<mi>d</mi>
<mi>m</mi>
</msub>
<mo>&CenterDot;</mo>
<msub>
<mi>v</mi>
<mi>m</mi>
</msub>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
</mtd>
</mtr>
<mtr>
<mtd>
<mtable>
<mtr>
<mtd>
<mrow>
<mi>s</mi>
<mo>.</mo>
<mi>t</mi>
<mo>.</mo>
</mrow>
</mtd>
<mtd>
<mrow>
<msub>
<mi>d</mi>
<mi>m</mi>
</msub>
<mo>=</mo>
<mn>0</mn>
<mo>,</mo>
<mn>1</mn>
<mo>;</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>M</mi>
</munderover>
<msub>
<mi>d</mi>
<mi>m</mi>
</msub>
<mo>&CenterDot;</mo>
<msub>
<mi>w</mi>
<mi>m</mi>
</msub>
<mo>&GreaterEqual;</mo>
<mn>0.85.</mn>
</mrow>
</mtd>
</mtr>
</mtable>
</mtd>
</mtr>
</mtable>
<mo>;</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>4</mn>
<mo>)</mo>
</mrow>
</mrow>
In formula：vmIt is the discriminating force coefficient of m-th of assessment dimension, can be calculated and obtained by assessment data；wmIt is by analytic hierarchy process (AHP)
The weight of m-th of the assessment dimension determined；M is the dimension total number of primary election system；dmIt is 0-1 variables, when value is 0, represents
M-th of assessment dimension is deleted, when value is 1, represents to retain m-th of assessment dimension.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710267849.9A CN107133727A (en) | 2017-04-22 | 2017-04-22 | Dimensionality optimization method is assessed based on the failure effect for differentiating force coefficient |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710267849.9A CN107133727A (en) | 2017-04-22 | 2017-04-22 | Dimensionality optimization method is assessed based on the failure effect for differentiating force coefficient |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107133727A true CN107133727A (en) | 2017-09-05 |
Family
ID=59715965
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710267849.9A Pending CN107133727A (en) | 2017-04-22 | 2017-04-22 | Dimensionality optimization method is assessed based on the failure effect for differentiating force coefficient |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107133727A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108305014A (en) * | 2018-02-23 | 2018-07-20 | 国家电网公司 | A kind of failure model and effect analysis method based on reliability room and Rough Ideals point method |
| CN113449024A (en) * | 2021-06-23 | 2021-09-28 | 平安普惠企业管理有限公司 | Insurance data analysis method, device, equipment and medium based on big data |
-
2017
- 2017-04-22 CN CN201710267849.9A patent/CN107133727A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108305014A (en) * | 2018-02-23 | 2018-07-20 | 国家电网公司 | A kind of failure model and effect analysis method based on reliability room and Rough Ideals point method |
| CN108305014B (en) * | 2018-02-23 | 2021-12-03 | 国家电网公司 | Failure mode and influence analysis method based on reliability room and rough ideal point method |
| CN113449024A (en) * | 2021-06-23 | 2021-09-28 | 平安普惠企业管理有限公司 | Insurance data analysis method, device, equipment and medium based on big data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Dinmohammadi et al. | A fuzzy-FMEA risk assessment approach for offshore wind turbines | |
| Vinodh et al. | Application of FMEA to an automotive leaf spring manufacturing organization | |
| JP4550632B2 (en) | Equipment maintenance plan support system and support method thereof | |
| Wang et al. | Condition-based maintenance with scheduling threshold and maintenance threshold | |
| Rawat et al. | Productivity measurement of manufacturing system | |
| CN103793859B (en) | A kind of wind power plant operation monitoring and event integrated evaluating method | |
| CN105975797B (en) | A kind of product initial failure root primordium recognition methods based on Fuzzy data processing | |
| CN102848266B (en) | Machine tool spindle accuracy prediction method | |
| Sahu et al. | Benchmarking CNC machine tool using hybrid-fuzzy methodology: a multi-indices decision making (MCDM) approach | |
| Kobbacy et al. | A survey of AI in operations management from 2005 to 2009 | |
| CN102486833A (en) | Method for predicting efficiency and detecting fault of device | |
| CN107133727A (en) | Dimensionality optimization method is assessed based on the failure effect for differentiating force coefficient | |
| Abbate et al. | Maintenance Digital Twin using vibration data | |
| Dykes et al. | Effect of tip-speed constraints on the optimized design of a wind turbine | |
| CN106649755A (en) | Threshold self-adaption setting abnormity detection method for multi-dimensional real-time power transformation device data | |
| Usubamatov et al. | Mathematical models for productivity and availability of automated lines | |
| CN108038599A (en) | A kind of preventive maintenance cycle multi objective control method based on assay intervals | |
| Feng et al. | Predictive maintenance decision making based on reinforcement learning in multistage production systems | |
| Guo et al. | Analytical Formulation for Sizing and Estimating the Dimensions and Weight of Wind Turbine Hub and Drivetrain Components | |
| Vachon | Long-term O&M costs of wind turbines based on failure rates and repair costs | |
| Jiang et al. | Recent results on key performance indicator oriented fault detection using the DB-KIT toolbox | |
| Minh et al. | Optimized design of source energy for manufacturing machine by digital numerical control | |
| Sambrekar et al. | Maintenance strategies for realizing Industry 4.0: An overview | |
| May et al. | Condition based maintenance for offshore wind turbines: the effects of false alarms from condition monitoring systems | |
| CN105469148B (en) | Ship electromechanical equipment guarantee opportunity determination method |
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 | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20170905 |
|
| WD01 | Invention patent application deemed withdrawn after publication |