CN103823455A - Workshop scheduling simulation method based on equipment failure scheduling model - Google Patents
Workshop scheduling simulation method based on equipment failure scheduling model Download PDFInfo
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Abstract
The invention discloses a workshop scheduling simulation method based on an equipment failure scheduling model. The workshop scheduling simulation method comprises the following steps: establishing an equipment failure scheduling model and an operation model for performing data analysis, modifying the models, implementing tests, replacing data for performing the secondary simulation, analyzing the bottle neck, and analyzing the simulation result. According to the workshop scheduling simulation method based on the equipment failure scheduling model, provided by the invention, the possibility of successfully designing a workshop production system is increased, and the design cost and risks are reduced; the simulation result is verified by using an genetic algorithm, the design period of a traditional design is shortened from the aspect of time, the probability of the equipment failure is reduced, the defect produced by re-processing the product replacing equipment is lowered. The actual production model is applied to eM-Plant software and is converted into a model recognizable by the software, the time wasting for re-clamping is avoided, the stock-holding cost caused by the overstock waste of to-be-processed products is reduced, and liquidated damages and the reputation loss caused by delayed delivery are reduced.
Description
Technical field
The invention belongs to the technical field of Job-Shop emulation mode, relate in particular to a kind of Job-Shop emulation mode based on equipment failure scheduling model.
Background technology
Along with scientific and technical development, production scale is increasing, complicacy is more and more higher, market competition is also more and more fierce, therefore the management to enterprise and the monitoring to production run are all had higher requirement, in the face of different clients' multi-varieties and small-batch product demand, require manufacturing shop can tackle this dynamic diversity requirement, the problem that company manager and IE engineers face is: while how breaking down for workshop appliance, analyze the feature of Dynamic Job-shop Scheduling, analyze the impact that workshop appliance breaks down on Job-Shop scheduling result; How in the situation that order batch plan changes, production run to be controlled, so that the flexibility that performance is produced to greatest extent; How in the situation that the order duration changes, to manage, decision-making, make enterprise produce maximum overall economic efficiency etc.Concerning manufacturing enterprise, be the problem of having to face in order to place onself in an invincible position in competition, to reduce costs, and guarantee productive capacity and the efficiency that workshop is higher, be the task of top priority.The target of production scheduling is: the utilization factor, raising employee utilization factor, maximum profit, the expense that runs minimized, minimum investment, the maximum return that improve production equipment, shorten the production cycle of product, make plant capacity maximum, and device fails will inevitably produce negatively influencing to scheduling result.Good Job-Shop can make workshop accept and process a large amount of processing and manufacture the information such as resource within a short period of time, rational management and the configuration resources of production, with the shorter time, higher quality, lower cost and quality services obtain success Lai Shi enterprise and have the advantage in market competition on TQCS.Equipment failure rate is extremely important for production and processing, when production equipment breaks down, how more reasonably to use machinery and equipment, pendulum Industrial Engineer in face of.At present, traditional Job-Shop emulation mode exist the probability of device fails large, goods more the processing again of exchange device produce that ratio of defects is high, the clamping high problem of penalty that many, to overstock waste inventory costs and time delay are delivered goods of losing time again.
Along with scientific and technical development, production scale is increasing, complicacy is more and more higher, market competition is also more and more fierce, therefore the management to enterprise and the monitoring to production run are all had higher requirement, in the face of different clients' multi-varieties and small-batch product demand, require manufacturing shop can tackle this dynamic diversity requirement, while breaking down for workshop appliance, analyze the feature of Dynamic Job-shop Scheduling, analyze the impact that workshop appliance breaks down on Job-Shop scheduling result, make enterprise produce maximum overall economic efficiency etc.
Job-Shop is mainly for a decomposable job (as product manufacture), inquire under the prerequisite of As soon as possible Promising Policy constraint condition (as delivery date, process route, resource situation), by assigning production ordering, arrange its ingredient (operation) to use the sequencing of which resource, its process time and processing, to obtain the optimization of production time or cost.In theoretical research, Job-Shop Scheduling Problem is often called as sequencing problem or resource allocation problem or combinatorial optimization problem.
Summary of the invention
The object of the embodiment of the present invention is to provide a kind of Job-Shop emulation mode based on equipment failure scheduling model, be intended to solve that the probability that traditional Job-Shop emulation mode exists device fails is large, goods more the processing again of exchange device produce that ratio of defects is high, the clamping high problem of penalty that many, to overstock waste inventory costs and time delay are delivered goods of losing time again.
The embodiment of the present invention is to realize like this, a kind of Job-Shop emulation mode based on equipment failure scheduling model, the method by Workshop Production task is planned, Task-decomposing, Process fusion, process optimization, by production task dynamic decomposition become different levels, connect each other several there is the varigrained task of logical sequence, based on the fault model of each kind equipment, each production task is selected by equipment and is mated, distribute to most suitable equipment, Job-Shop is also with regard to dynamic formation like this.
Further, the method steps flow chart comprise apparatus for establishing fault scheduling model, moving model carry out data analysis, revise model, implement test, change data carry out secondary simulation, analyze bottleneck, analyze simulation result;
Described apparatus for establishing fault scheduling model refers to opens Plant Simulation 8.1 softwares, set up a Frame, in model layer, insert research object, simulation time is set, and simulation time is continuous 100h, i.e. 4d4h, then model global variable is set, programme by Method, finally determine and parameter complete modeling process;
Described moving model carries out data analysis and refers to and open EventController, moving model, and the data analysis such as operation output quantity and output capacity to process time, single emulation; .
Described modification model refers to take last work station as example, work station failure rate is discussed and is changed how to affect output capacity, by clicking model layer master menu Toos, in drop-down menu, select Custom Attribute, increase by two variable: Availability5 and MTTR5, be type real, change the value of Availability simultaneously, revise Reset, operation EventController, finally shows operation result;
Described enforcement test refers to that output capacity OutRate_Line2 using the second production line is as system index y, equipment failure rate Availability5 is an x who affects y, relation between x and y through discussion, generates relation and regression equation between equipment failure rate and production capacity;
Described replacing data are carried out secondary simulation and are referred in the time changing data the plant factor from 70% to 100% at last work station and change, the output of the second production line will change, the variation relation of output and throughput rate also can change, and obtains changing Availability5 after data and the regression equation of OutRate_Line2 by emulation for the second time;
Described analysis bottleneck refers to that the failure rate of every machine does not cause obvious impact in capital to output capacity, changes by model parameter being done to some, analyzes failure rate the having the greatest impact to output capacity of which platform machine;
Described analysis simulation result refers to and utilizes genetic algorithm, by the equipment of processing sequence, analyze the regularity of distribution of running time, stand-by period, blocking time and equipment failure time on every equipment, and analyze unit fault between workstation without working area in the situation that, the impact of the failure rate of the impact of multimachine fault on system produce, bottleneck operation on system produce rate.
Further, the model global variable of the setting in described apparatus for establishing fault scheduling model can be divided into two classes: need to show information and can show information, generally, the global variable of the information that need not show adopts clicks model layer master menu Tools, in drop-down menu, select Custom Attribute, in the dialog box ejecting, click New button, eject variable-definition dialog box, define respectively global variable (or being called attribute) by variable and data type, define rear if modify, the operations such as deletion, select respectively " Edit → Delete " to carry out,
Further, Method in described apparatus for establishing fault scheduling model programming has two streamlines, above one be called Line1, add up the output of Line1 with variable Output_Line1; One is called Line2 below, add up the output of Line2 with variable Output_Line2, with the ratio of Output_Line2 and Output_Line1, as two line output ratios, the concrete steps of Method programming comprise: double-click CalOutPut, input SimTalk statement; Double-click Drain1, input and click OK button after CalOutPut and exit in the text box after Entrance, the setting operation of Drain2 is identical; Double-click Reset and open, between do and end, insert " Set_Vars "; Double-click Set_Vars operation, just can carry out parameter to model and be provided with;
Further, the described Job-Shop emulation mode based on equipment failure scheduling model has been studied two production lines 1 and production line 2, on every production line, there are 5 a certain products A of device fabrication, in the time that the equipment failure rate (breaking down) of equipment M25 changes, and servicing time is certain, the relation between research equipment utilization factor and output and production efficiency.
Effect gathers
Job-Shop emulation mode based on equipment failure scheduling model provided by the invention, selecting the equipment failure of Dynamic Job-shop is research object, reduce the complexity of design effort, improved the successfully possibility of production system between designing car, reduced the cost and risk of design; By apparatus for establishing fault scheduling model, utilize em-plant to analyze the impact that workshop appliance breaks down on Job-Shop scheduling result, and verify simulation result by genetic algorithm, shorten design cycle of traditional design from the time, reduce the probability of device fails, reduced the more defect that processing produces again of exchange device of goods; Actual production model is applied to and on eM-Plant software, converts it into the model that software can be identified, avoid the time that clamping is wasted again, reduce the inventory cost of wasting that overstocks that processed product causes, reduced time delay the deliver goods penalty that causes and the loss of prestige.
Accompanying drawing explanation
Fig. 1 is the flow chart of steps of the Job-Shop emulation mode based on equipment failure scheduling model that provides of the embodiment of the present invention.
Embodiment
In order to make object of the present invention, technical scheme and advantage clearer, below in conjunction with embodiment, the present invention is further elaborated.Should be appreciated that specific embodiment described herein, only in order to explain the present invention, is not intended to limit the present invention.
The method by Workshop Production task is planned, Task-decomposing, Process fusion, process optimization etc., by production task dynamic decomposition become different levels, connect each other several there is the varigrained task of logical sequence, based on the fault model of each kind equipment, each production task is selected by equipment and is mated, distribute to most suitable equipment, Job-Shop is also with regard to dynamic formation like this.The logic existing between production task and sequential relationship, determined the relation between equipment; The decomposition level structure of production task, has determined the level of Job-Shop equally.
Logical sequence relation between the attributes such as the I/O of task division, task and task has formed the hierarchical structure of Job-Shop.The method is according to equipment failure model supports dynamic job shop scheduling, and Job-Shop planning hockets with enforcement.Can be according to workshop appliance actual state, scheduling process between emulation car.
Because bottom in hierarchy adopts relatively independent production run, for production task relatively independent in production task decomposition texture, the variation of its production run does not affect the production run on its upper strata, reduces the impact of equipment failure on whole production task; Same by changing the whole process at production run restructural lower floor's production run place, upper strata, improve robustness and the flexibility of Job-Shop.
Task-decomposing-equipment selection-Process fusion mechanism can adapt to the impact, rapid adjustment or reconstruction task decomposition texture, institutional framework and process planning and the enforcement that happen suddenly and unscheduled event (as equipment shortage, equipment failure, production task change etc.) causes Workshop Production.
Below in conjunction with drawings and the specific embodiments, application principle of the present invention is further described.
As shown in Figure 1, a Job-Shop emulation mode based on equipment failure scheduling model, the method steps flow chart comprises that apparatus for establishing fault scheduling model S101, moving model carry out data analysis S102, revise model S103, implement test S104, change data and carry out secondary simulation S105, analyze bottleneck S106, analyze simulation result S107;
Described apparatus for establishing fault scheduling model S101 refers to and opens Plant Simulation 8.1 softwares, set up a Frame, in model layer, insert research object, simulation time is set, and simulation time is continuous 100h, i.e. 4d4h, then model global variable is set, programme by Method, finally determine and parameter complete modeling process;
Described moving model carries out data analysis S102 and refers to and open EventController, moving model, and the data analysis such as operation output quantity and output capacity to process time, single emulation;
Described modification model S103 refers to take last work station as example, work station failure rate is discussed and is changed how to affect output capacity, by clicking model layer master menu Toos, in drop-down menu, select Custom Attribute, increase by two variable: Availability5 and MTTR5, be type real, change the value of Availability simultaneously, revise Reset, operation EventController, finally shows operation result;
Described enforcement test S104 refers to that output capacity OutRate_Line2 using the second production line is as system index y, equipment failure rate Availability5 is an x who affects y, relation between x and y through discussion, generates relation and regression equation between equipment failure rate and production capacity;
Described replacing data are carried out secondary simulation S105 and are referred in the time changing data the plant factor from 70% to 100% at last work station and change, the output of the second production line will change, the variation relation of output and throughput rate also can change, and obtains changing Availability5 after data and the regression equation of OutRate_Line2 by emulation for the second time;
Described analysis bottleneck S106 refers to that the failure rate of every machine does not cause obvious impact in capital to output capacity, changes by model parameter being done to some, analyzes failure rate the having the greatest impact to output capacity of which platform machine;
Described analysis simulation result S107 refers to and utilizes genetic algorithm, by the equipment of processing sequence, analyze the regularity of distribution of running time, stand-by period, blocking time and equipment failure time on every equipment, and analyze unit fault between workstation without working area in the situation that, the impact of the failure rate of the impact of multimachine fault on system produce, bottleneck operation on system produce rate.
Further, the model global variable of the setting in described apparatus for establishing fault scheduling model S101 can be divided into two classes: need to show information and can show information, generally, the global variable of the information that need not show adopts clicks model layer master menu Tools, in drop-down menu, select Custom Attribute, in the dialog box ejecting, click New button, eject variable-definition dialog box, define respectively global variable (or being called attribute) by variable and data type, define rear if modify, the operations such as deletion, select respectively " Edit → Delete " to carry out.
Described apparatus for establishing fault scheduling model refers to opens Plant Simulation 8.1 softwares, set up a Frame, in model layer, insert research object, simulation time is set, and simulation time is continuous 100h, i.e. 4d4h, then model global variable is set, programme by Method, finally determine and parameter complete modeling process; Concrete operations are as follows:
1 opens Plant Simulation 8.1 softwares, sets up a Frame, and insertion objects in model layer couples together each object with Connector object.
(1) EventController arranges, and simulation time is continuous 100h, i.e. 4d4h.
(2) method Reset is system initialization object, belongs to systems approach, and common practices is to be renamed as Reset after inserting a Method, and then icon has just become system icon.
(3) method Set_Vars belongs to user-defined method, generally adopts the Method of blue icon to represent the method for directly not moving; Shown in green Method represents directly to move.
2 arrange model global variable
In Plant Simulation 8.1, generally use Information Flow(information flow object) in Variable object carry out defining variable, these variablees are placed in model layer.In the time that global variable is many, may cause the layout in model layer to show more chaotic.If global variable is classified and will be found to be divided into two classes: need to show information and can show information.Generally, recommend the global variable of the information that need not show to adopt mode below to define.
(1) click model layer master menu Tools, in drop-down menu, select Custom Attribute.
(2) in the dialog box ejecting, click New button, eject variable-definition dialog box, by or table 1 shown in variable and data type define respectively this 5 global variables (or being called attribute), if will modify after having defined, the operation such as deletion, select respectively " Edit → Delete " to carry out.
The implication of the global variable in table 1 model layer
| Name variable | Initial value | Data type | Implication |
| Availability | 95 | Real number | Machine availability |
| MTTR | 600 | Real number | Fault mean repair time |
| ProcTimes | 60 | Real number | Equipment process time |
| SigMa | 2 | Real number | The standard deviation (s) of fluctuation process time is the ProcTimes number percent representation of process time |
3 Method programmings
Method programming has two streamlines, above one be called Line1, add up the output of Line1 with variable Output_Line1; One is called Line2 below, adds up the output of Line2 with variable Output_Line2,, represents with OutRate_Line2 as two line output ratios with the ratio of Output_Line2 and Output_Line1.Suppose that Line1 is perfect condition production line (non-fault, process time are long value and fluctuate without other), therefore, also can think that OutRate_Line2 is exactly the output capacity of production line 2.
Further, Method in described apparatus for establishing fault scheduling model S101 programming has two streamlines, above one be called Line1, add up the output of Line1 with variable Output_Line1; One is called Line2 below, add up the output of Line2 with variable Output_Line2, with the ratio of Output_Line2 and Output_Line1, as two line output ratios, the concrete steps of Method programming comprise: double-click CalOutPut, input SimTalk statement; Double-click Drain1, input and click OK button after CalOutPut and exit in the text box after Entrance, the setting operation of Drain2 is identical; Double-click Reset and open, between do and end, insert " Set_Vars "; Double-click Set_Vars operation, just can carry out parameter to model and be provided with.
Further, the described Job-Shop emulation mode based on equipment failure scheduling model has been studied two production lines 1 and production line 2, on every production line, there are 5 a certain products A of device fabrication, in the time that the equipment failure rate (breaking down) of equipment M25 changes, and servicing time is certain, the relation between research equipment utilization factor and output and production efficiency.
Dynamic job shop scheduling problem model is as follows:
Be provided with m machining cell C={C
1, C
2... C
m, each machining cell is made up of Nc platform equipment, and the equipment processing ability in unit exchanges.There is n processing tasks J={J simultaneously
1, J
2... J
n, require to be respectively delivery date D={D
1, D
2..., D
n.Processing tasks J
ioperation be: J
ij (Pij), wherein, i is corresponding to processing tasks sequence number i=1 ..., n, j is corresponding to the operation number of each task, if use Q
irepresent the operation sum of i task, J=1 ..., Q
i.P
ijrepresent processing tasks J
ij procedure machining cell (i=1 ..., n; J=1 ..., Q
i; P
ij∈ { C
1, C
2..., C
m).Operation J
ij (Pij)process time be T
ij.
Model agreement:
1) process time of the every procedure of each processing tasks is known, and immutable in the time that operation is sorted;
2) operation is sorted based on process constraint, and the manufacturing procedure of each processing tasks maintains fixing sequencing, is also operation J
ij (Pij)after completing, its next process J
i, j+1 (Pi, j+1)could start;
3) be processing tasks J
ij procedure J
ij (Pij)specify the machining cell P at place
ij;
4) every process equipment can only be processed a procedure of a processing tasks simultaneously;
Make M
ijmachining cell P
ijfor processing tasks J
ij road J
ij (Pij)the process equipment that operation is distributed, SS ij represents processing tasks J
jj procedure J
ij (Pij)start time, SE ij represents processing tasks J
ij road J
ij (Pij)the completion date of operation.:
SS ij+T
ij≤SE ij≤SS i,j+1 1.1
If machining cell P
ijcorresponding operating crew's system is determined utilizes the time to integrate as U
ij:
SS ij，SE ij∈U
ij 1.2
Meanwhile, the optimization aim function of Job Scheduling according to the actual requirements, can be different, as:
Mean transit time is the shortest:
Min{(ΣSE i,Qi)/n} 1.3
Delay the shortest delivery date:
Min{Σmax(SE i,Qi-D
i,0)} 1.4
Completion date is the shortest:
Min{Σmax(SE i,Qi)} 1.5
Therefore, the target of Job Scheduling is, under set target, as the shortest in mean transit time, can guarantee each processing tasks on each device resource according to the requirement processing of the manufacturing procedure of this task.
Because device fails will inevitably produce a series of impacts to manufacturing schedule, as goods more exchange device again processing produce defect; Again the time that clamping is wasted; Need the overstocked inventory cost of wasting that converted products causes; And time delay the deliver goods penalty that causes and loss of prestige etc.
While breaking down for workshop appliance, analyze the feature of Dynamic Job-shop Scheduling, eM-Plant is applied to job-shop scheduling problem, by analogue simulation actual condition, analyze the impact that workshop appliance breaks down on Job-Shop scheduling result.
By apparatus for establishing fault scheduling model, utilize em-plant to analyze the impact that workshop appliance breaks down on Job-Shop scheduling result, and verify simulation result by genetic algorithm.
The first step that realizes the Job Shop Scheduling based on emulation is to set up the realistic model of system, in eM-Plant, workpiece to be processed belongs to mobile object (MU), utilize the Entity of mobile unit to carry out modeling, general machining cell can be used SingleProc modeling, can be set the process time of this machining cell in SingleProc, setup time, failure recovery time etc., the action that workpiece passes in and out this machining cell can also be set, can carry out emulation to process equipment easily, divide flow object F1owControl to serve as parts machining process yardman's role, it is according to the processing technology of workpiece, be responsible for workpiece to deliver in corresponding machining cell.The processing tasks of needs scheduling is designed in the TableFile of " processing tasks table " by name, this TableFile is made up of 5 row, 1-4 row have recorded respectively the release time of workpiece, MU unit, workpiece quantity and workpiece title used, the attribute of the 5th row of table is a TableFile object, record workpiece machining information, mainly comprising machining process route, the data that workpiece is optimized at the needs such as preparation and process time, workpiece processing cost of each machining cell etc. of workpiece." next process inspection " and " operation judgement " is respectively SingleProc and Method object, they can determine that the workpiece next one is by the machining cell of being thrown according to the process route of the workpiece in processing tasks table, as completion of processing, flow to Drain unit, complete this workpiece processing.
Principle of work
As shown in Figure 1, a kind of Job-Shop emulation mode steps flow chart based on equipment failure scheduling model comprises that apparatus for establishing fault scheduling model S101, moving model carry out data analysis S102, revise model S103, implement test S104, change data and carry out secondary simulation S105, analyze bottleneck S106, analyze simulation result S107; Described apparatus for establishing fault scheduling model S101 refers to and opens Plant Simulation 8.1 softwares, set up a Frame, in model layer, insert research object, simulation time is set, and simulation time is continuous 100h, i.e. 4d4h, then model global variable is set, programme by Method, finally determine and parameter complete modeling process; Described moving model carries out data analysis S102 and refers to and open EventController, moving model, and the data analysis such as operation output quantity and output capacity to process time, single emulation; Described modification model S103 refers to take last work station as example, work station failure rate is discussed and is changed how to affect output capacity, by clicking model layer master menu Toos, in drop-down menu, select Custom Attribute, increase by two variable: Availability5 and MTTR5, be type real, change the value of Availability simultaneously, revise Reset, operation EventController, finally shows operation result; Described enforcement test S104 refers to that output capacity OutRate_Line2 using the second production line is as system index y, equipment failure rate Availability5 is an x who affects y, relation between x and y through discussion, generates relation and regression equation between equipment failure rate and production capacity; Described replacing data are carried out secondary simulation S105 and are referred in the time changing data the plant factor from 70% to 100% at last work station and change, the output of the second production line will change, the variation relation of output and throughput rate also can change, and obtains changing Availability5 after data and the regression equation of OutRate_Line2 by emulation for the second time; Described analysis bottleneck S106 refers to that the failure rate of every machine does not cause obvious impact in capital to output capacity, changes by model parameter being done to some, analyzes failure rate the having the greatest impact to output capacity of which platform machine; Described analysis simulation result S107 refers to and utilizes genetic algorithm, by the equipment of processing sequence, analyze the regularity of distribution of running time, stand-by period, blocking time and equipment failure time on every equipment, and analyze unit fault between workstation without working area in the situation that, the impact of the failure rate of the impact of multimachine fault on system produce, bottleneck operation on system produce rate.
The foregoing is only preferred embodiment of the present invention, not in order to limit the present invention, all any modifications of doing within the spirit and principles in the present invention, be equal to and replace and improvement etc., within all should being included in protection scope of the present invention.
Claims (8)
1. the Job-Shop emulation mode based on equipment failure scheduling model, it is characterized in that, the method by Workshop Production task is planned, Task-decomposing, Process fusion, process optimization, by production task dynamic decomposition become different levels, connect each other several there is the varigrained task of logical sequence, based on the fault model of each kind equipment, each production task is selected by equipment and is mated, and distributes to most suitable equipment, and Job-Shop is also with regard to dynamic formation like this.
2. the Job-Shop emulation mode based on equipment failure scheduling model as claimed in claim 1, it is characterized in that, the method concrete steps flow process comprise apparatus for establishing fault scheduling model, moving model carry out data analysis, revise model, implement test, change data carry out secondary simulation, analyze bottleneck, analyze simulation result;
Apparatus for establishing fault scheduling model, by setting up a Frame, inserts research object in model layer, and simulation time is set, simulation time is continuous 100h, i.e. then 4d4h arranges model global variable, programme by Method, finally determine and parameter complete modeling process;
Moving model carries out data analysis and refers to and open EventController, moving model, and operation output quantity and output capacity data analysis to process time, single emulation;
Revising model refers to take last work station as example, work station failure rate is discussed and is changed how to affect output capacity, by clicking model layer master menu Toos, in drop-down menu, select Custom Attribute, increase by two variable: Availability5 and MTTR5, be type real, change the value of Availability simultaneously, revise Reset, operation EventController, finally shows operation result;
Implement test and refer to that output capacity OutRate_Line2 using the second production line is as system index y, equipment failure rate Availability5 is an x who affects y, relation between x and y through discussion, generates relation and regression equation between equipment failure rate and production capacity;
Changing data carries out secondary simulation and refers in the time changing data the plant factor from 70% to 100% at last work station and change, the output of the second production line will change, the variation relation of output and throughput rate also can change, and obtains changing Availability5 after data and the regression equation of OutRate_Line2 by emulation for the second time;
Analyze bottleneck and refer to that the failure rate of every machine does not cause obvious impact in capital to output capacity, change by model parameter being done to some, analyze failure rate the having the greatest impact to output capacity of any platform machine;
Analysis simulation result refers to and utilizes genetic algorithm, by the equipment of processing sequence, analyze the regularity of distribution of running time, stand-by period, blocking time and equipment failure time on every equipment, and analyze unit fault between workstation without working area in the situation that, the impact of the failure rate of the impact of multimachine fault on system produce, bottleneck operation on system produce rate.
3. the Job-Shop emulation mode based on equipment failure scheduling model as claimed in claim 1, it is characterized in that, the model global variable of the setting in described apparatus for establishing fault scheduling model can be divided into two classes: need to show information and can show information, the global variable of the information that need not show adopts clicks model layer master menu Tools, in drop-down menu, select Custom Attribute, in the dialog box ejecting, click New button, eject variable-definition dialog box, define respectively global variable by variable and data type, define rear if modify, deletion action, select respectively " Edit → Delete " to carry out.
4. the Job-Shop emulation mode based on equipment failure scheduling model as claimed in claim 1, it is characterized in that, Method in described apparatus for establishing fault scheduling model programming has two streamlines, above one be called Line1, add up the output of Line1 with variable Output_Line1; One is called Line2 below, add up the output of Line2 with variable Output_Line2, with the ratio of Output_Line2 and Output_Line1, as two line output ratios, the concrete steps of Method programming comprise: double-click CalOutPut, input SimTalk statement; Double-click Drain1, input and click OK button after CalOutPut and exit in the text box after Entrance, the setting operation of Drain2 is identical; Double-click Reset and open, between do and end, insert Set_Vars; Double-click Set_Vars operation, model is carried out to parameter and be provided with.
5. the Job-Shop emulation mode based on equipment failure scheduling model as claimed in claim 1, is characterized in that, the logical sequence relation between I/O attribute and the task of task division, task has formed the hierarchical structure of Job-Shop.
6. the Job-Shop emulation mode based on equipment failure scheduling model as claimed in claim 1, it is characterized in that, the method is according to equipment failure model supports dynamic job shop scheduling, Job-Shop planning hockets with enforcement, can be according to workshop appliance actual state, scheduling process between emulation car.
7. the Job-Shop emulation mode based on equipment failure scheduling model as claimed in claim 1, it is characterized in that, because bottom in hierarchy adopts relatively independent production run, for production task relatively independent in production task decomposition texture, the variation of its production run does not affect the production run on its upper strata, reduces the impact of equipment failure on whole production task; Same by changing the whole process at production run restructural lower floor's production run place, upper strata, improve robustness and the flexibility of Job-Shop.
8. the Job-Shop emulation mode based on equipment failure scheduling model as claimed in claim 1, it is characterized in that, Task-decomposing-equipment selection-Process fusion mechanism can adapt to the impact, rapid adjustment or reconstruction task decomposition texture, institutional framework and process planning and the enforcement that happen suddenly and unscheduled event causes Workshop Production.
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| CN104408525A (en) * | 2014-11-11 | 2015-03-11 | 西北工业大学 | Quantitative evaluation and control method of job shop scheduling risks |
| CN104484733A (en) * | 2014-11-12 | 2015-04-01 | 广东工业大学 | Manufacturing shop operation adaptive scheduling method and device |
| CN105183573A (en) * | 2015-10-09 | 2015-12-23 | 北京大学 | Online identification method and system for high-frequency consecutive failure tasks in cloud computing system |
| CN105512401A (en) * | 2015-12-08 | 2016-04-20 | 中机中联工程有限公司 | Make-to-order based worker shift arrangement simulation method |
| CN105824304A (en) * | 2016-05-18 | 2016-08-03 | 重庆大学 | Flexible job shop dynamic scheduling method taking availability of machining equipment into consideration |
| CN106019195A (en) * | 2016-07-22 | 2016-10-12 | 国网浙江省电力公司电力科学研究院 | Electric power measurement automation verification assembly line fault diagnosis system |
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| CN107870611A (en) * | 2016-09-28 | 2018-04-03 | 横河电机株式会社 | Workshop analogue means and workshop analogy method |
| CN109884996A (en) * | 2019-02-02 | 2019-06-14 | 宁波吉利汽车研究开发有限公司 | Production control system, method and production management system |
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| CN110501978A (en) * | 2018-05-18 | 2019-11-26 | 中国科学院沈阳自动化研究所 | A kind of robot product workshop scheduled production dispatching method |
| CN111062535A (en) * | 2019-12-16 | 2020-04-24 | 中国工程物理研究院化工材料研究所 | Method and system for realizing dynamic scheduling of energetic material production process |
| CN113034047A (en) * | 2021-04-21 | 2021-06-25 | 河南工业职业技术学院 | Flexible manufacturing workshop optimal scheduling method and system |
| CN113075915A (en) * | 2021-03-31 | 2021-07-06 | 西安建筑科技大学 | Em-plant based virtual simulation implementation method, system and equipment |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104408525A (en) * | 2014-11-11 | 2015-03-11 | 西北工业大学 | Quantitative evaluation and control method of job shop scheduling risks |
| CN104408525B (en) * | 2014-11-11 | 2018-01-09 | 西北工业大学 | The quantitative evaluation and control method of solving job shop scheduling problem risk |
| CN104484733A (en) * | 2014-11-12 | 2015-04-01 | 广东工业大学 | Manufacturing shop operation adaptive scheduling method and device |
| CN107079269B (en) * | 2014-11-28 | 2021-01-01 | 索尼公司 | Information processing apparatus, information processing method, and computer program |
| CN107079269A (en) * | 2014-11-28 | 2017-08-18 | 索尼公司 | Message processing device, information processing method and program |
| CN105183573A (en) * | 2015-10-09 | 2015-12-23 | 北京大学 | Online identification method and system for high-frequency consecutive failure tasks in cloud computing system |
| CN105183573B (en) * | 2015-10-09 | 2017-12-01 | 北京大学 | The ONLINE RECOGNITION method and system of the continuous failure task of cloud computing system medium-high frequency time |
| CN105512401A (en) * | 2015-12-08 | 2016-04-20 | 中机中联工程有限公司 | Make-to-order based worker shift arrangement simulation method |
| CN105824304A (en) * | 2016-05-18 | 2016-08-03 | 重庆大学 | Flexible job shop dynamic scheduling method taking availability of machining equipment into consideration |
| CN106019195A (en) * | 2016-07-22 | 2016-10-12 | 国网浙江省电力公司电力科学研究院 | Electric power measurement automation verification assembly line fault diagnosis system |
| CN106019195B (en) * | 2016-07-22 | 2019-02-05 | 国网浙江省电力公司电力科学研究院 | Electric power measurement automation verification assembly line fault diagnosis system |
| CN107870611A (en) * | 2016-09-28 | 2018-04-03 | 横河电机株式会社 | Workshop analogue means and workshop analogy method |
| CN110501978A (en) * | 2018-05-18 | 2019-11-26 | 中国科学院沈阳自动化研究所 | A kind of robot product workshop scheduled production dispatching method |
| CN109884996A (en) * | 2019-02-02 | 2019-06-14 | 宁波吉利汽车研究开发有限公司 | Production control system, method and production management system |
| CN109884996B (en) * | 2019-02-02 | 2021-01-05 | 宁波吉利汽车研究开发有限公司 | Production control system, method and production management system |
| CN110348148A (en) * | 2019-07-16 | 2019-10-18 | 北京航空航天大学 | A kind of Key experiments process recognition methods of Kernel-based methods FMEA |
| CN110348148B (en) * | 2019-07-16 | 2021-02-19 | 北京航空航天大学 | Key test process identification method based on process FMEA |
| CN111062535A (en) * | 2019-12-16 | 2020-04-24 | 中国工程物理研究院化工材料研究所 | Method and system for realizing dynamic scheduling of energetic material production process |
| CN113075915A (en) * | 2021-03-31 | 2021-07-06 | 西安建筑科技大学 | Em-plant based virtual simulation implementation method, system and equipment |
| CN113034047A (en) * | 2021-04-21 | 2021-06-25 | 河南工业职业技术学院 | Flexible manufacturing workshop optimal scheduling method and system |
| CN113034047B (en) * | 2021-04-21 | 2023-06-30 | 河南工业职业技术学院 | Flexible manufacturing workshop optimal scheduling method and system |
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