CN106127358A - A kind of manufacture system prediction method for maintaining of task based access control reliability state - Google Patents
A kind of manufacture system prediction method for maintaining of task based access control reliability state Download PDFInfo
- Publication number
- CN106127358A CN106127358A CN201610664177.0A CN201610664177A CN106127358A CN 106127358 A CN106127358 A CN 106127358A CN 201610664177 A CN201610664177 A CN 201610664177A CN 106127358 A CN106127358 A CN 106127358A
- Authority
- CN
- China
- Prior art keywords
- equipment
- maintenance
- task
- reliability
- access control
- 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
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 151
- 238000000034 method Methods 0.000 title claims abstract description 60
- 238000012423 maintenance Methods 0.000 claims abstract description 130
- 238000005259 measurement Methods 0.000 claims abstract description 25
- 239000000203 mixture Substances 0.000 claims abstract description 10
- 238000009472 formulation Methods 0.000 claims abstract description 9
- 238000012545 processing Methods 0.000 claims abstract description 8
- 230000000737 periodic effect Effects 0.000 claims abstract description 5
- 201000004569 Blindness Diseases 0.000 claims abstract description 4
- 238000012797 qualification Methods 0.000 claims description 12
- 230000000694 effects Effects 0.000 claims description 11
- 238000009826 distribution Methods 0.000 claims description 9
- 230000001186 cumulative effect Effects 0.000 claims description 8
- 230000008569 process Effects 0.000 claims description 6
- 238000004458 analytical method Methods 0.000 claims description 5
- 230000005540 biological transmission Effects 0.000 claims description 5
- 238000000354 decomposition reaction Methods 0.000 claims description 5
- 230000007850 degeneration Effects 0.000 claims description 5
- 238000001514 detection method Methods 0.000 claims description 5
- 238000012372 quality testing Methods 0.000 claims description 5
- 230000007246 mechanism Effects 0.000 claims description 4
- 238000012360 testing method Methods 0.000 claims description 4
- 238000003369 Quality Function Deployment Methods 0.000 claims description 3
- 230000007547 defect Effects 0.000 claims description 3
- 230000008439 repair process Effects 0.000 claims description 3
- 230000007423 decrease Effects 0.000 claims description 2
- 238000010586 diagram Methods 0.000 description 8
- 238000005457 optimization Methods 0.000 description 6
- 230000000875 corresponding effect Effects 0.000 description 5
- 238000011161 development Methods 0.000 description 4
- 230000018109 developmental process Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 230000008901 benefit Effects 0.000 description 3
- 230000002596 correlated effect Effects 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 230000032683 aging Effects 0.000 description 1
- 230000033228 biological regulation Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 208000001491 myopia Diseases 0.000 description 1
- 230000004379 myopia Effects 0.000 description 1
- 230000003449 preventive effect Effects 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
- 230000001568 sexual effect Effects 0.000 description 1
- 230000000007 visual effect Effects 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
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- 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
- G06Q10/20—Administration of product repair or maintenance
-
- 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)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Theoretical Computer Science (AREA)
- Tourism & Hospitality (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Entrepreneurship & Innovation (AREA)
- Game Theory and Decision Science (AREA)
- Development Economics (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)
- General Factory Administration (AREA)
Abstract
The manufacture system prediction method for maintaining of a kind of task based access control reliability state, its step is as follows: one, sets up and manufactures system-based data base；Two, utilize basic data that equipment performance variation tendency and each relevant parameter are analyzed；Three, pre-measurement equipment corrective maintenance cost；Four, prediction facilities plan maintenance cost；Five, prediction equipment processing ability failure costs；Six, the prediction indirect failure costs of equipment；Seven, prediction device product mass loss expense；Eight, prediction comprehensive cost, determines this equipment task reliability thresholds, and then determines optimum prediction maintenance policy；Nine, according to the result of step 8, determining a upper equipment task requirement, repeating step 28, until completing the formulation of whole manufacture system prediction maintenance policy；Ten, interpretation of result；By above step, reach the engineering purpose of equipment performance combinations of states production task, solved tradition condition maintenarnce and ignore the problem of production status and the blindness problem of periodic maintenance.
Description
Technical field
The invention provides the manufacture system prediction method for maintaining of a kind of task based access control reliability state, belong to production pipe
Reason field.
Background technology
System reliability and availability and then guarantee production efficiency, product quality, the pass of enterprise profit is manufactured as improving
Key measure, the maintenance policy manufacturing system is always the emphasis that manufacturing enterprise pays close attention to.According to statistics, usual maintenance of equipment expense accounts for
The 15%-40% of manufacturing cost, and along with automatization, the development of intellectualized technology, its in year the amplitude of rising be up to 10%-
15%.Therefore, formulation reasonably manufacture system prediction maintenance policy has become enterprise and has cut operating costs, and improves the market competition
The important means of power.
Along with information technology and the fast development of computational science and the extensive application in intelligence manufacture field, industrial undertaking
Equipment day by day complicate, precise treatment, intellectuality, manufacture system maintenance policy be faced with new opportunities and challenges.From system
From the perspective of engineering, the direct service object manufacturing system is production task, and the manufacture system of stable operation is to ensure that product
Quality and the antecedent condition at date of delivery, manufacturing the production schedule and equipment task in the formulation process of system maintenance strategy is to neglect
Depending on, there is the natural relation that influences each other between maintenance and production activity.Modern manufacturing system mostly is complicated multiplexing
Position manufactures system, and due to the equipment wear and aging phenomenon that the moment occurs in running, manufacture system itself has intrinsic many
State property characteristic, the most changeable production task requirement, make the description to manufacturing system production status more difficult.Additionally, manufacture
There is the functional structure relation determined by production technology in system between each equipment, there is task phase in the maintenance of each equipment
The complex relationship such as Guan Xing, economical dependence, these phenomenons are that maintenance work brings huge challenge.Reasonably manufacture system dimension
Repair strategy and there is very important status in process of production, be to ensure that enterprise carries out the premise of high-quality, low-cost production, as
What prediction manufacture system production status, and then it is raw to adapt to formulate prospective maintenance strategy targetedly according to concrete production task
The dynamic dispatching of product activity is the sciences problems that manufacture field is generally acknowledged.
Present stage, correction maintenance can not meet production requirement, manufactures the research of system maintenance strategy with preventative maintenance
It is main, condition maintenarnce and periodically (periodically) maintenance can be divided into.Condition maintenarnce method is more concern equipment degeneration shape own
State, based on equipment basic reliability state set up manufacture system maintenance strategy, this method ignore undoubtedly from production task
And the requirement of product quality and restriction, lack practicality；Periodic maintenance is then based on system operation time, sets up manufacture system
The optimal preventative maintenance cycle, this method is widely used in actual production, but ignores method itself and have ignored and be
System running status, frequently results in maintenance surplus and causes unnecessary economic loss, or maintenance affects production not in time, even makes
Become security incident.The polymorphism of manufacture system can not be considered from system engineering angle for existing Research Thinking, it is impossible to
Formulate the limitation of practicable maintenance policy for enterprise, this patent proposes the manufacture system of a kind of task based access control reliability state
System prospective maintenance method: by definition manufacture system task reliability (manufacture system under prescribed conditions with in the stipulated time
Complete ability (the i.e. R of regulation production taskd)) fusion device performance state and actual production mission requirements, scientifically to describe
The production status of manufacture system, and then with minimum comprehensive cost as criterion, in conjunction with mission requirements in each relative stations of manufacture system
Between transmission, analyze the optimum prediction maintenance policy of each equipment of current manufacturing system successively.The method is the most more
Mend traditional preventative maintenance method not enough.The manufacture system prediction of a kind of task based access control reliability state that the present invention is given
Method for maintaining, has paid close attention to the production status of whole manufacture system on the whole, has ensured the productivity effect of enterprise with this.With this reason
The enforcement of opinion guidance system manufacturing system plant maintenance activity, can meet raising equipment dependability and availability, ensure production safety,
Ensure the requirement that production task is timely completed, the production expenses of enterprises can be reduced again.
Summary of the invention
(1) purpose of the present invention:
For in the past based on the manufacture system shortsightedness maintenance producing the performance state of equipment own or operation hours
The deficiency of strategy, the present invention provides a kind of new manufacture system maintenance policy development method reliable character of one task based access control
The manufacture system prediction method for maintaining of state.With in given planning time section and the manufacture system of clear and definite and concrete production task is pre-
Survey property maintenance policy be established as visual angle, according to manufacture system task reliability intension, set up mission reliability and equipment performance
Incidence relation between degenerate state；And then estimation is under certain mission reliability threshold value, may produce in planning time
By corrective maintenance cost, planned maintenance expense, equipment capacity loss, cannot be timely completed between production task causes
Connect economic loss and the comprehensive cost of product quality loss composition, and then obtain under different task reliability thresholds, produce
The change curve of the comprehensive cost produced in planning horizon, determines the optimal maintenance policy of equipment.Further, task based access control requirement
Reverse transmission in manufacture system, sets up multistation and manufactures the prospective maintenance strategy of system.
(2) technical scheme:
The present invention is the manufacture system prediction method for maintaining of a kind of task based access control reliability state, the basic assumption of proposition
As follows:
There is a detection station after assuming 1 every process equipment of manufacture system, and testing result is cocksure；
Assume 2 only quality testing qualified can enter next station at goods；
Assume between the 3 manufacture each equipment of system separate；
Carrying out corrective maintenance when assuming 4 device fails immediately, use minimal maintenance mode, its effect is to recover to set
Received shipment row, does not affect the variation tendency of equipment performance；
Assume that 5 prospective maintenance are the faulty planned maintenance set in advance, it is possible to improve equipment performance but can not make
Equipment recovers as new；
Assume that 6 equipment are brand-new state when planning time starts, and the fault rate of equipment obeys Weibull distribution；
Assume that the ratio of all types of fault modes that 7 equipment occur is constant, and the repair time of all types of fault
The performance state current with equipment is unrelated；
Based on above-mentioned it is assumed that the manufacture system prediction maintenance side of a kind of task based access control reliability state that proposes of the present invention
Method, its step is as follows:
Step 1, foundation manufacture system-based data base；
Step 2, utilize basic data that equipment performance variation tendency and each relevant parameter are analyzed, and analysis task can
Lean on the incidence relation between equipment performance degeneration；
Step 3, the pre-measurement equipment corrective maintenance cost in planning time section；
Step 4, the pre-measurement equipment planned maintenance expense in planning time section；
Step 5, the pre-measurement equipment working ability failure costs in planning time section；
Step 6, the pre-measurement equipment indirect loss expense in planning time section；
Step 7, the pre-measurement equipment product quality failure costs in planning time section；
Step 8, pre-measurement equipment comprehensive cost in planning time section, determine this equipment task reliability thresholds, and then
Determine optimum prediction maintenance policy；
Step 9, result according to step 8, determine a upper equipment task requirement, repeats step 2-8, until completing whole
Manufacture the formulation of system prediction maintenance policy；
Step 10, interpretation of result.
Wherein, " set up and manufacture system-based data base " described in step 1, refer to according to product Critical to quality
Decomposition map identify manufacture system relevant device, be then based on the big data of commercial production, collect the basic number of each relevant device
According to, including equipment fault data, history mantenance data, quality testing data and operation detection data etc..Carry on the back at intelligence manufacture
Under scape, such data can obtain from network high in the clouds easily.
Wherein, described in step 2 " basic data is utilized equipment performance variation tendency and each relevant parameter to be carried out point
Analysis ", refer to determine equipment failure rate variation tendency λ according to basic datak+1(t)=bkλk(t+aktk), a herekRepresent that the life-span passs
Subtracting coefficient, 0 ＜ ak＜ 1；bkRepresent that fault increases the factor, bk＞ 1；tkRepresent kth time prospective maintenance cycle time.According to base
Plinth data determine qualification rate variation tendency ρk(t)=ρ0-γλk(t), here ρ0Represent that under brand-new state, the manufacture of equipment is qualified
Rate, γ represents a constant coefficient.So, equipment manufacture qualification rate expectation within the kth time prospective maintenance cycle can represent
For:
Wherein, " incidence relation between analysis task reliability and equipment performance degeneration " described in step 2, refer to
Associating between mission reliability with equipment performance (cumulative failure probability) is set up according to manufacturing system task reliability intension
System, and the maintenance of equipment mechanism of task based access control reliability state is proposed, as shown in Figure 1；Manufacture system task reliability and processing
Capability state distribution and probability are directly related, the relation between working ability distributions and probability and equipment cumulative failure probability
It is represented by:
Here,Expression equipment degree of unavailability, CiMRepresent maximum working ability state, PixRepresent equipment processing ability
State is CixProbability, τ represents expectation maintenance time of single corrective
Here δ(i,e)Represent the probability that fault mode e occurs,The maintenance time of fault mode e.
Wherein, " pre-measurement equipment corrective maintenance cost in planning time section " described in step 3, refer to basis
A certain given mission reliability threshold value, calculates device fails in planning time section and carries out corrective maintenance and produced
Expense c1, expression isHere ccRepresent that single corrects the expected value of maintenance cost,
E represents planning time section (0, T) interior prospective maintenance periodicity, and ε represents that last predictability (plan) maintenance terminates to rule
Draw the remaining time of time period endHere Nk=1, τ ' represent the time used by single planned maintenance.
Wherein, " pre-measurement equipment planned maintenance expense in planning time section " described in step 4, refer to based on appointing
Business reliability thresholds, calculates the planned maintenance number of times in planning time section, and then calculates expense c produced by planned maintenance2,
Expression formula isHere cpRepresent the expected value of single planned maintenance expense.
Wherein, " pre-measurement equipment working ability failure costs in planning time section " described in steps of 5, refer to estimate
Calculation equipment causes shutting down produced loss c due to maintenance3, expression formula is
Here lpRepresenting productivity's loss of energy that single planned maintenance causes, θ representation unit production capacity reduces corresponding loss cost.
Wherein, " pre-measurement equipment indirect loss expense in planning time section " described in step 6, refer to by producing
Task is not timely completed caused enterprise indirect economic loss c4, cause order including the compensation that exceeds the time limit, goodwill decline
Reduce.Expression formula is:
Here, σ represents that indirect loss is expected, relevant to concrete production task, expert be given after evaluating and testing；RiTExpression equipment
The mission reliability threshold value of (i), RiεRepresent the mission reliability in remaining time ε.
Wherein, " pre-measurement equipment product quality failure costs in planning time section " described in step 7, refer to estimate
Calculate the production loss c caused due to product quality defect5, expression formula is:
Here, d represents that production task requires (the qualified products quantity of output in the unit interval),Represent pre-
The manufacture qualification rate expectation of equipment (i) in the property surveyed predetermined period,The manufacture of equipment (i) in expression section ε remaining time
Qualification rate is expected,Represent the production loss that individual defect product is corresponding.
Wherein, " pre-measurement equipment comprehensive cost in planning time section " described in step 8, determine this equipment task
Reliability thresholds, and then determine optimum prediction maintenance policy, refer to by MATLAB computed in software different task reliability threshold
Comprehensive cost c=c under Zhi1+c2+c3+c4+c5, determine optimal mission reliability threshold value with the minimum principle of comprehensive cost, and then
Obtain prospective maintenance strategy (t1, t2, t3..., tE-1)。
Wherein, described in step 9 " according to the result of step 8, determine a upper equipment task requirement, repeat step
2-8, until completing the formulation of whole manufacture system prediction maintenance policy ", refer to the mission reliability threshold according to current device
Value, determines current device manufacture qualification rate expectation in planning time sectionUtilize(setting with rework operation
Standby) obtain the input requirements of current device, it is an output requirement producing equipment, is sequentially completed every
The formulation of the prospective maintenance strategy of platform relevant device.
Wherein, " interpretation of result " described in step 10, is by this method acquired results and tradition condition maintenarnce, cycle
The result of property method for maintaining compares.
By above step, the multistation establishing task based access control reliability state manufactures system prediction method for maintaining,
Reach the engineering purpose of equipment performance combinations of states actual production task, solved tradition condition maintenarnce and be concerned only with equipment self
State and ignore the problem of practical production status and the blindness problem of periodic maintenance, and then reduce in production activity due to
The economic loss that decision-making deviation causes, enterprise productivity effect and competitiveness.
(3) the manufacture system prediction method for maintaining of a kind of task based access control reliability state of the present invention, it uses
Method is as follows:
Step 1, Critical to quality according to product, the decomposition utilizing quality function deployment to carry out Critical to quality is reflected
Penetrate, identify related process and the equipment of production, and then set up the manufacture system-based data base towards this production task；
Step 2, equipment Foundations data are analyzed, estimate the value of each parameter；
Step 3, the corrective maintenance cost calculated under different task reliability thresholds；
Step 4, the planned maintenance expense calculated under different task reliability thresholds；
Equipment processing ability loss under step 5, calculating different task reliability thresholds；
Step 6, the indirect loss calculated under different task reliability thresholds；
Step 7, the product quality loss calculated under different task reliability thresholds；
Step 8, calculating comprehensive cost, determine mission reliability threshold value corresponding during comprehensive cost minimum, and calculate execution
The timing node of planned maintenance.
Step 9, task based access control require the reverse transmission in manufacture system, determine the mission requirements of previous station, then
Repeat step 2-8.
Step 10, utilize U.S.'s MATLAB software emulation, to this patent method and tradition preventative maintenance method contrast.
(4) advantage and effect:
The present invention is the manufacture system prediction method for maintaining of a kind of task based access control reliability state, and its advantage is:
1 >. the present invention considers emphatically the polymorphism problem of manufacture system, breaches tradition condition maintenarnce and periodically ties up
The one-sidedness repaiied and blindness problem.
2 >. the present invention has taken into full account that multistation manufactures the functional relationship between each equipment of system, utilizes mission requirements
Reverse transmission, gives the prospective maintenance policy development method that multistation manufactures system.
3 >. the present invention requires as starting point have high specific aim, science and practicality with concrete production task.
Accompanying drawing explanation
Fig. 1 is the maintenance of equipment mechanism of task based access control reliability state.
Fig. 2 is the method for the invention flow chart.
Fig. 3 is the corrective maintenance cost changing trend diagram with mission reliability threshold value.
Fig. 4 is the planned maintenance expense changing trend diagram with mission reliability threshold value.
Fig. 5 is the equipment capacity failure costs changing trend diagram with mission reliability threshold value.
Fig. 6 is the indirect loss expense changing trend diagram with mission reliability threshold value.
Fig. 7 is the product quality failure costs changing trend diagram with mission reliability threshold value.
Fig. 8 is the comprehensive cost changing trend diagram with mission reliability threshold value.
Fig. 9 is the comprehensive cost changing trend diagram with preventative maintenance Ct value.
Figure 10 is the equipment correlated population expense changing trend diagram with equipment cumulative failure probability threshold value.
In figure, symbol description is as follows:
Refer to the input load of equipment i；
Refer to the output certified products number of equipment i；
Detailed description of the invention
With example, the present invention is described in further details below in conjunction with the accompanying drawings.
The present invention is the manufacture system prediction method for maintaining of a kind of task based access control reliability state, as shown in Figure 2, in fact
Execute step as follows:
Step 1 collects the product quality information of certain model four cylinder diesel engine cylinder head.Quality function deployment is utilized to enter
The decomposition of row Critical to quality maps, and identifies that engine cylinder cap manufactures system related keyword technique and the equipment of production, sees below
Table 1.Collect the fault of each related processing equipment, maintenance, quality testing the most respectively and run the data such as detection.
Table 1. Critical to quality and manufacturing process information thereof
Step 2 is to equipment a5Basic data be analyzed, according to the maintenance of equipment mechanism of task based access control reliability, such as figure
Shown in 1, estimate the value of each relevant parameter.
Fault rate obeys Weibull distribution: λ1(t)=(m/ η) (t/ η)m-1, m=3 here, η=100, t represents predictability
Operation hours after maintenance；Life-span decrement factor a1=a2=...=aE=0.1, fault upscaling factor b1=b2=...=bE
=1.1；
Manufacture qualification rate: ρk(t)=ρ0-γλk(t), here ρ0=0.99, γ=0.03；
Working ability distributions and probability:
Sx=0,20,40,60,80,100,120,140,160,180,200},
Px={ P0,P1,P2,P3,P4,P5,P6,P7,P8,P9,P10,
Can be obtained by all kinds of fault rates: P0=P1=P2=3P3=5P4=7P5=7P6=10P7=12P8=17P9
And
Time parameter: τ=0.424 is time-consumingly expected in corrective maintenance；Planned maintenance τ '=0.4；
Cost parameter: cc=300, lp=80, cp=50, θ=0.8,σ=2000；
Production task: d=150/ days；
Planning time section: T=150 days.
Step 3 calculates the corrective maintenance cost under different task reliability thresholds.From degree of unavailability equation, equipment
Cumulative failure probability and equipment processing ability distribution probability one_to_one corresponding, so when given specific tasks require, task is reliable
Sexual state and equipment cumulative failure probability are then in one-to-one relationship, in present case, based on each parameter obtained in step 2
Value, obtain existing between two parameter numerical value relation:This formula does not have physical significance.Take task
Reliability thresholds optimization range is (0.5,1), and the variation tendency of corrective maintenance cost is as shown in Figure 3.
Step 4 calculates the planned maintenance expense under different task reliability thresholds.Take mission reliability threshold optimization scope
For (0.5,1), the variation tendency of planned maintenance expense is as shown in Figure 4.
Step 5 calculates equipment capacity loss expense under different task reliability thresholds.Take mission reliability threshold optimization model
Enclosing for (0.5,1), the variation tendency of capacity loss expense is as shown in Figure 5.
Step 6 calculates the indirect loss expense under different task reliability thresholds.Take mission reliability threshold optimization scope
For (0.5,1), the variation tendency of indirect loss expense is as shown in Figure 6.
Step 7 calculates the product quality failure costs under different task reliability thresholds.Take mission reliability threshold optimization
Scope is (0.5,1), and the variation tendency of product quality failure costs is as shown in Figure 7.
Step 8 calculates comprehensive cost, and taking mission reliability threshold optimization scope is (0.5,1), and its some numerical results is such as
Shown in table 2 below.The variation tendency of comprehensive cost is as shown in Figure 8.
Table 2. some numerical results
Optimum results is: as equipment a5Mission reliability threshold value when taking 0.958, equipment a5Combining for this production task
Close network minimal, for c=965.54, in this case, carry out 4 planned maintenances in planning time section domestic demand, respectively: t1=
39.15；t2=34.02；t3=29.52；t4=25.60
Step 9 is according to equipment a5Prospective maintenance strategy, equipment a can be obtained4For meeting final task requirement, its point of task
Require d4=151.8, then repeat step 1-8, final result is as shown in table 3 by that analogy.
Table 3. optimum results
Step 10 utilizes MATLAB software emulation, to this patent method and tradition preventative maintenance method contrast.With equipment
a5As a example by, use preventive maintenance method, its comprehensive cost with the planned maintenance cycle variation tendency as shown in Figure 9.Use
Condition maintenarnce method based on equipment performance, does not consider concrete production status, and now equipment correlated population expense only includes correcting
Property maintenance, planned maintenance and equipment capacity lose three kinds, its equipment correlated population expense is with the change of equipment cumulative failure probability
Trend is as shown in Figure 10.
Analyze three optimum maintenance policies of these three method for maintaining gained further, and contrast three optimum maintenance policies
Corresponding comprehensive cost, as shown in table 4.
Table 4. optimum results contrasts
The more existing two kinds of preventative maintenance methods of the inventive method have obvious advantage, this is because the present invention be
Propose on the basis of fully realizing manufacture system polymorphism, and require as starting point with concrete production task, relatively other two weeks
Method has more preferable specific aim, science and practicality, it is possible to instructs enterprise to formulate rational equipment Maintenance Policy, reduces enterprise
Industry production cost.
Claims (11)
1. a manufacture system prediction method for maintaining for task based access control reliability state, the basic assumption of proposition is as follows:
There is a detection station after assuming 1 every process equipment of manufacture system, and testing result is cocksure；
Assume 2 only quality testing qualified can enter next station at goods；
Assume between the 3 manufacture each equipment of system separate；
Carrying out corrective maintenance when assuming 4 device fails immediately, use minimal maintenance mode, its effect is restorer fortune
OK, the variation tendency of equipment performance is not affected；
Assume that 5 prospective maintenance are the faulty planned maintenance set in advance, it is possible to improve equipment performance but equipment can not be made
Recover as new；
Assume that 6 equipment are brand-new state when planning time starts, and the fault rate of equipment obeys Weibull distribution；
Assume that the ratio of all types of fault modes that 7 equipment occur is constant, and the repair time of all types of fault with set
Standby current performance state is unrelated；
Based on above-mentioned it is assumed that the manufacture system prediction method for maintaining of a kind of task based access control reliability state that proposes of the present invention,
It is characterized in that: implementation step is as follows:
Step one, foundation manufacture system-based data base；
Step 2, utilize basic data that equipment performance variation tendency and each relevant parameter are analyzed, and analysis task is reliable
And the incidence relation between equipment performance degeneration；
Step 3, the pre-measurement equipment corrective maintenance cost in planning time section；
Step 4, the pre-measurement equipment planned maintenance expense in planning time section；
Step 5, the pre-measurement equipment working ability failure costs in planning time section；
Step 6, the pre-measurement equipment indirect loss expense in planning time section；
Step 7, the pre-measurement equipment product quality failure costs in planning time section；
Step 8, pre-measurement equipment comprehensive cost in planning time section, determine this equipment task reliability thresholds, and then determine
Optimum prediction maintenance policy；
Step 9, result according to step 8, determine a upper equipment task requirement, repeats step 2-8, until completing whole system
The formulation of manufacturing system prospective maintenance strategy；
Step 10, interpretation of result；It is that this method acquired results is opposed with tradition condition maintenarnce, the result of periodic maintenance method
Ratio；
By above step, the multistation establishing task based access control reliability state manufactures system prediction method for maintaining, reaches
The engineering purpose of equipment performance combinations of states actual production task, solves tradition condition maintenarnce and is concerned only with equipment oneself state
And ignore the problem of practical production status and the blindness problem of periodic maintenance, and then reduce in production activity due to decision-making
The economic loss that deviation causes, enterprise productivity effect and competitiveness.
The manufacture system prediction method for maintaining of a kind of task based access control reliability state the most according to claim 1, it is special
Levy and be:
In " set up and manufacture system-based data base " described in step one, refer to that the decomposition according to product Critical to quality is reflected
Penetrate identification manufacture system relevant device, be then based on the big data of commercial production, collect the basic data of each relevant device, including setting
Standby fault data, history mantenance data, quality testing data and operation detection data etc.；Under intelligence manufacture background, such
Data obtain from network high in the clouds.
The manufacture system prediction method for maintaining of a kind of task based access control reliability state the most according to claim 1, it is special
Levy and be:
" utilizing basic data to be analyzed equipment performance variation tendency and each relevant parameter " described in step 2, refers to
Equipment failure rate variation tendency λ is determined according to basic datak+1(t)=bkλk(t+aktk), a herekExpression life-span decrement factor, 0
＜ ak＜ 1；bkRepresent that fault increases the factor, bk＞ 1；tkRepresent kth time prospective maintenance cycle time；True according to basic data
Determine qualification rate variation tendency ρk(t)=ρ0-γλk(t), here ρ0Representing the manufacture qualification rate of equipment under brand-new state, γ represents
One constant coefficient；So, equipment manufacture qualification rate Expectation-based Representation for Concepts within the kth time prospective maintenance cycle is:
Wherein, " incidence relation between analysis task reliability and equipment performance degeneration " described in step 2, refer to root
The incidence relation between mission reliability and equipment performance i.e. cumulative failure probability is set up according to manufacturing system task reliability intension,
And the maintenance of equipment mechanism of task based access control reliability state is proposed；Manufacture system task reliability and working ability distributions and
Probability is directly related, and the relational representation between working ability distributions and probability and equipment cumulative failure probability is:
Here,Expression equipment degree of unavailability, CiMRepresent maximum working ability state, PixRepresent equipment processing ability state
For CixProbability, τ represents expectation maintenance time of single correctiveThis
In δ (i,e) represent the probability that fault mode e occurs,The maintenance time of fault mode e.
The manufacture system prediction method for maintaining of a kind of task based access control reliability state the most according to claim 1, it is special
Levy and be:
" pre-measurement equipment corrective maintenance cost in planning time section " described in step 3, refers to according to a certain given
Mission reliability threshold value, calculate device fails in planning time section and carry out the corrective produced expense of maintenance
c1, expression isHere ccRepresenting that single corrects the expected value of maintenance cost, E represents
Planning time section (0, T) interior prospective maintenance periodicity, ε represents that last predictability planned maintenance terminates to planning time section
The remaining time of endHere Nk=1, τ ' represent the time used by single planned maintenance.
The manufacture system prediction method for maintaining of a kind of task based access control reliability state the most according to claim 1, it is special
Levy and be:
" pre-measurement equipment planned maintenance expense in planning time section " described in step 4, refers to task based access control reliability
Threshold value, calculates the planned maintenance number of times in planning time section, and then calculates expense c produced by planned maintenance2, expression formula isHere cpRepresent the expected value of single planned maintenance expense.
The manufacture system prediction method for maintaining of a kind of task based access control reliability state the most according to claim 1, it is special
Levy and be:
" pre-measurement equipment working ability failure costs in planning time section " described in step 5, refer to estimation device by
Cause shutting down produced loss c in maintenance3, expression formula isHere lp
Representing productivity's loss of energy that single planned maintenance causes, θ representation unit production capacity reduces corresponding loss cost.
The manufacture system prediction method for maintaining of a kind of task based access control reliability state the most according to claim 1, it is special
Levy and be:
" pre-measurement equipment indirect loss expense in planning time section " described in step 6, referring to can not by production task
It is timely completed caused enterprise indirect economic loss c4, cause order to reduce including the compensation that exceeds the time limit, goodwill decline, express
Formula is:
Here, σ represents that indirect loss is expected, relevant to concrete production task, expert be given after evaluating and testing；RiTExpression equipment (i)
Mission reliability threshold value, RiεRepresent the mission reliability in remaining time ε.
The manufacture system prediction method for maintaining of a kind of task based access control reliability state the most according to claim 1, it is special
Levy and be:
" pre-measurement equipment product quality failure costs in planning time section " described in step 7, refers to estimate owing to producing
The production loss c that quality defect causes5, expression formula is:
Here, d represents that production task requires (the qualified products quantity of output in the unit interval),Represent that predictability is pre-
The manufacture qualification rate expectation of equipment (i) in the survey cycle,The manufacture qualification rate of equipment (i) in expression section ε remaining time
Expect,Represent the production loss that individual defect product is corresponding.
The manufacture system prediction method for maintaining of a kind of task based access control reliability state the most according to claim 1, it is special
Levy and be:
" pre-measurement equipment comprehensive cost in planning time section " described in step 8, determines this equipment task reliability threshold
Value, and then determine optimum prediction maintenance policy, refer to by combining under MATLAB computed in software different task reliability thresholds
Conjunction expense c=c1+c2+c3+c4+c5, determine optimal mission reliability threshold value with the minimum principle of comprehensive cost, and then predicted
Property maintenance policy (t1, t2, t3..., tE-1)。
The manufacture system prediction method for maintaining of a kind of task based access control reliability state the most according to claim 1, it is special
Levy and be:
Described in step 9 " according to the result of step 8, determine a upper equipment task requirement, repeat step 2-8, until
Complete the formulation of whole manufacture system prediction maintenance policy ", refer to the mission reliability threshold value according to current device, determine and work as
The manufacture qualification rate expectation in planning time section of the front equipmentUtilize(the equipment with rework operation) obtain the input requirements of current device, it is an output requirement producing equipment, is sequentially completed every
The formulation of the prospective maintenance strategy of relevant device.
The manufacture system prediction method for maintaining of 11. a kind of task based access control reliability state according to claim 1, it is special
Levy and be: its using method is as follows:
Step 1, Critical to quality according to product, the decomposition utilizing quality function deployment to carry out Critical to quality maps,
Identify related process and the equipment of production, and then set up the manufacture system-based data base towards this production task；
Step 2, equipment Foundations data are analyzed, estimate the value of each parameter；
Step 3, the corrective maintenance cost calculated under different task reliability thresholds；
Step 4, the planned maintenance expense calculated under different task reliability thresholds；
Equipment processing ability loss under step 5, calculating different task reliability thresholds；
Step 6, the indirect loss calculated under different task reliability thresholds；
Step 7, the product quality loss calculated under different task reliability thresholds；
Step 8, calculating comprehensive cost, determine mission reliability threshold value corresponding during comprehensive cost minimum, and calculate implement plan
The timing node of maintenance；
Step 9, task based access control require the reverse transmission in manufacture system, determine the mission requirements of previous station, then repeat
Step 2-8；
Step 10, utilize U.S.'s MATLAB software emulation, to this patent method and tradition preventative maintenance method contrast.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610664177.0A CN106127358A (en) | 2016-08-12 | 2016-08-12 | A kind of manufacture system prediction method for maintaining of task based access control reliability state |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610664177.0A CN106127358A (en) | 2016-08-12 | 2016-08-12 | A kind of manufacture system prediction method for maintaining of task based access control reliability state |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106127358A true CN106127358A (en) | 2016-11-16 |
Family
ID=57258728
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610664177.0A Pending CN106127358A (en) | 2016-08-12 | 2016-08-12 | A kind of manufacture system prediction method for maintaining of task based access control reliability state |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106127358A (en) |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107729405A (en) * | 2017-09-25 | 2018-02-23 | 中国航空工业集团公司西安飞机设计研究所 | A kind of calibration cycle generation method of ATE |
| CN107958293A (en) * | 2017-11-29 | 2018-04-24 | 上海交通大学 | Towards the service outsourcing chance maintaining method of lease metaplasia production |
| CN108805302A (en) * | 2018-06-14 | 2018-11-13 | 合肥工业大学 | A kind of manufacturing equipment approaches of predictive maintenance and system |
| CN109376881A (en) * | 2018-12-12 | 2019-02-22 | 中国航空工业集团公司上海航空测控技术研究所 | Complication system repair determining method based on maintenance cost optimization |
| CN109858689A (en) * | 2019-01-21 | 2019-06-07 | 北京航空航天大学 | A kind of Product Assembly system health risk analysis method of reliability guiding |
| CN110084401A (en) * | 2019-03-21 | 2019-08-02 | 中车工业研究院有限公司 | A kind of method for optimizing scheduling and device based on reserved maintenance time |
| CN110235069A (en) * | 2017-02-07 | 2019-09-13 | 首要金属科技奥地利有限责任公司 | The integrated planning of production plan and/or maintenance plan |
| CN110427712A (en) * | 2019-08-07 | 2019-11-08 | 广东工业大学 | A kind of preventative maintenance method and Shop Floor based on failure effect analysis (FEA) |
| CN110728043A (en) * | 2019-09-29 | 2020-01-24 | 东南大学 | Ship lock maintenance plan making method based on average use cost in expected year |
| CN111882080A (en) * | 2020-07-08 | 2020-11-03 | 天津理工大学 | State-based workpiece production equipment maintenance monitoring method |
| CN112215369A (en) * | 2020-09-18 | 2021-01-12 | 岭东核电有限公司 | Method, device, equipment and storage medium for determining effectiveness of nuclear power plant maintenance |
-
2016
- 2016-08-12 CN CN201610664177.0A patent/CN106127358A/en active Pending
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110235069A (en) * | 2017-02-07 | 2019-09-13 | 首要金属科技奥地利有限责任公司 | The integrated planning of production plan and/or maintenance plan |
| US11281196B2 (en) | 2017-02-07 | 2022-03-22 | Primetals Technologies Austria GmbH | Integrated planning of production and/or maintenance plans |
| CN107729405A (en) * | 2017-09-25 | 2018-02-23 | 中国航空工业集团公司西安飞机设计研究所 | A kind of calibration cycle generation method of ATE |
| CN107958293A (en) * | 2017-11-29 | 2018-04-24 | 上海交通大学 | Towards the service outsourcing chance maintaining method of lease metaplasia production |
| CN107958293B (en) * | 2017-11-29 | 2021-08-27 | 上海交通大学 | Service outsourcing opportunity maintenance method for leasing production |
| CN108805302A (en) * | 2018-06-14 | 2018-11-13 | 合肥工业大学 | A kind of manufacturing equipment approaches of predictive maintenance and system |
| CN108805302B (en) * | 2018-06-14 | 2020-07-17 | 合肥工业大学 | Manufacturing equipment predictive maintenance method and system |
| CN109376881A (en) * | 2018-12-12 | 2019-02-22 | 中国航空工业集团公司上海航空测控技术研究所 | Complication system repair determining method based on maintenance cost optimization |
| CN109376881B (en) * | 2018-12-12 | 2022-06-03 | 中国航空工业集团公司上海航空测控技术研究所 | Maintenance cost optimization-based complex system maintenance decision method |
| CN109858689A (en) * | 2019-01-21 | 2019-06-07 | 北京航空航天大学 | A kind of Product Assembly system health risk analysis method of reliability guiding |
| CN110084401B (en) * | 2019-03-21 | 2021-04-23 | 中车工业研究院有限公司 | Scheduling optimization method and device based on reserved maintenance time |
| CN110084401A (en) * | 2019-03-21 | 2019-08-02 | 中车工业研究院有限公司 | A kind of method for optimizing scheduling and device based on reserved maintenance time |
| CN110427712A (en) * | 2019-08-07 | 2019-11-08 | 广东工业大学 | A kind of preventative maintenance method and Shop Floor based on failure effect analysis (FEA) |
| CN110728043A (en) * | 2019-09-29 | 2020-01-24 | 东南大学 | Ship lock maintenance plan making method based on average use cost in expected year |
| CN111882080A (en) * | 2020-07-08 | 2020-11-03 | 天津理工大学 | State-based workpiece production equipment maintenance monitoring method |
| CN112215369A (en) * | 2020-09-18 | 2021-01-12 | 岭东核电有限公司 | Method, device, equipment and storage medium for determining effectiveness of nuclear power plant maintenance |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106127358A (en) | A kind of manufacture system prediction method for maintaining of task based access control reliability state | |
| Zhang et al. | Opportunistic maintenance strategy for wind turbines considering weather conditions and spare parts inventory management | |
| CN107122832A (en) | A kind of manufacture system preventative maintenance method of Quality Control And Reliability analysis | |
| CN111291963B (en) | Park comprehensive energy system planning method for coordinating economy and reliability | |
| CN106099993B (en) | A kind of power source planning method for adapting to new energy and accessing on a large scale | |
| CN109492777A (en) | A kind of Wind turbines health control method based on machine learning algorithm platform | |
| CN104850916A (en) | Improved-gray-Markov-model-based power equipment fault prediction method | |
| CN105354614A (en) | Big data based power grid information operation and maintenance active early-warning method | |
| CN103595076A (en) | Method for active power distribution for improving fatigue evenness of wind generating sets | |
| CN102930344A (en) | Method for forecasting ultra-short term bus load based on load trend changes | |
| CN103489044B (en) | A kind of generation risk control method of bidding of smart grid-oriented | |
| CN109245176B (en) | Risk-considering interconnected power grid unit combination method containing large-scale wind power | |
| CN110533299B (en) | Calculation method, equipment and medium for on-line monitoring of ammeter misalignment rate | |
| CN105427005A (en) | Operation risk assessment method of wind power station | |
| CN105226650A (en) | Based on the micro-capacitance sensor reliability calculation method of miniature combustion engine-energy storage cooperation strategy | |
| CN102646982A (en) | Low-carbon power generation dispatching method for wind farm | |
| CN106485596A (en) | A kind of controller switching equipment Strategies of Maintenance optimization method | |
| CN112070395B (en) | Energy Internet reliability assessment system, model establishment method and assessment method | |
| CN106611243A (en) | Residual correction method for wind speed prediction based on GARCH (Generalized ARCH) model | |
| CN110427689B (en) | Method for monitoring and diagnosing gas turbine unit group based on new information technology | |
| Li et al. | Reliability modeling and assessment for integrated energy system: a review of the research status and future prospects | |
| CN116796633A (en) | Power grid monitoring model correction method based on digital twin technology | |
| Wang et al. | Neural network applications in hybrid data-model driven dynamic frequency trajectory prediction for weak-damping power systems | |
| Li et al. | Research on System Integration Alliance of Urban Rail Transit Safety Monitoring. | |
| Shi et al. | Comprehensive Energy Efficiency Evaluation of Distributed Energy System Model Based on Entropy Weight Method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20161116 |
|
| RJ01 | Rejection of invention patent application after publication |