CN104808629A - Flexible robot manufacturing unit scheduling method - Google Patents
Flexible robot manufacturing unit scheduling method Download PDFInfo
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- CN104808629A CN104808629A CN201510187503.9A CN201510187503A CN104808629A CN 104808629 A CN104808629 A CN 104808629A CN 201510187503 A CN201510187503 A CN 201510187503A CN 104808629 A CN104808629 A CN 104808629A
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- 238000004519 manufacturing process Methods 0.000 title claims abstract description 56
- 238000000034 method Methods 0.000 title claims abstract description 32
- 230000002068 genetic effect Effects 0.000 claims abstract description 15
- 238000013178 mathematical model Methods 0.000 claims abstract description 4
- 238000003780 insertion Methods 0.000 claims description 3
- 230000037431 insertion Effects 0.000 claims description 3
- 230000035772 mutation Effects 0.000 claims description 3
- 230000017105 transposition Effects 0.000 claims description 3
- 238000003754 machining Methods 0.000 abstract description 2
- 238000005457 optimization Methods 0.000 abstract description 2
- 238000010845 search algorithm Methods 0.000 abstract 1
- 230000003044 adaptive effect Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 238000012546 transfer Methods 0.000 description 3
- 238000011160 research Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000012141 concentrate Substances 0.000 description 1
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/41865—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
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- 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
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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- Manufacturing & Machinery (AREA)
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- Multi-Process Working Machines And Systems (AREA)
Abstract
The invention provides a flexible robot manufacturing unit scheduling method. The flexible robot manufacturing unit scheduling method comprises the following steps of establishing a mathematical model and a disjunction model according to characters and machining procedures of a robot manufacturing unit; determining an object function and a solution range of schedule optimization, initializing population through a genetic algorithm, determining a group of codes according to the genetic algorithm, finding a critical path for the disjunction algorithm and obtaining an optimal solution within neighborhood of the critical path. According to the flexible robot manufacturing unit scheduling method, the shortest time of completion is solved through an algorithm combining a genetic algorithm and a domain search algorithm, scheduling of the flexible robot is convenient, the production efficiency is effectively improved, and production costs are greatly saved.
Description
Technical field
The present invention relates to flexible robot manufacturing cell dispatching technique field, be specifically related to a kind of dispatching method of flexible robot manufacturing cell.
Background technology
Along with the fast development of CIM Technology, traditional manufacture there occurs great and deep change, it is more and more expensive that social development makes manual labor become, and its production efficiency is low, in order to existence and development in the market competition of fierceness, enterprise starts to apply automatic producing technology to enhance productivity, industrial robot arises at the historic moment, transfer robot is the one application of industrial robot, it is by increasing the forms such as carrying guide rail, the transhipment of object can be realized flexibly fast, thus manufacturing industry is widely used in, flexible robot manufacturing cell is exactly by transfer robot, lathe, the novel intelligent manufacturing system of the hardware such as carrying guide rail and control software design composition as shown in Figure 1, it can significantly improve production efficiency, flexible robot manufacturing cell creates new production scheduling problems in the application process of enterprise, correlative study most both at home and abroad at present concentrates on traditional Job-Shop Job-Shop Scheduling Problem, and it is still few to the flexible robot manufacturing cell scheduling problem research of enterprise's utilization, therefore the scheduling problem studying the artificial unit processed of flexible machine more meets the Production requirement of modern enterprise.
Summary of the invention
In order to solve the problems of the technologies described above, the present invention, on traditional Job-Shop plant working Research foundation, proposes a kind of dispatching method applying the flexible robot manufacturing cell that genetic algorithm combines with field searching algorithm.
The technical solution used in the present invention is:
The dispatching method of a kind of flexible robot manufacturing cell provided by the present invention, comprises the following steps:
A. according to the feature of robot building unit and manufacturing procedure founding mathematical models and extracting figure model, that determines the objective function of optimizing scheduling and Optimized Operation solves scope, using the inverse of described target function value as fitness function, determine that minimizing completion date is optimizing scheduling target;
B. apply genetic algorithm initialization population, and the individuality in described population is evaluated, obtain colony of future generation through selection, intersection, mutation operator;
C. according to the group coding that described genetic algorithm is determined, find out the critical path of described extracting figure, and the lathe block found out in described critical path and robot block, by the relative position of manufacturing procedure in lathe block in mobile critical path, exchange carrying operation in critical path in robot block, adjustment task matching builds search neighborhood;
D. the optimum solution in critical path neighborhood is obtained.
Further, the genetic algorithm adopted in described step B is three layer scheduling methods that heuristic carrying operation insertion and heuristic carrying task matching method combine.
Further, the rule that in mobile critical path in step C, in lathe block, the relative position of manufacturing procedure is observed is: the aft-loaded airfoil that in lathe block, non-first manufacturing procedure is processed before moving to all manufacturing procedures or in lathe block, non-final one procedure moves to all manufacturing procedures, calculate the objective function of mobile rear gained each time, if it is more excellent, record.
Further, the rule that carrying operation in exchange critical path in step C in robot block is observed is: the carrying operation of robot block position respectively with the carrying operation transposition of its back location, calculate the objective function of gained after exchanging each time, if it is more excellent, record.
Further, the adjustment task matching in step C observes the heuristic rule that adjacent carrying operation distributes to different machines people, calculates the objective function of the rear gained of adjustment each time, if it is more excellent, and record.
Beneficial effect of the present invention is:
The hybrid algorithm that the dispatching method application genetic algorithm of a kind of flexible robot manufacturing cell provided by the present invention combines with field searching algorithm determines the shortest completion date, the convenient scheduling to flexible robot, effectively improve production efficiency, save production cost greatly.
Accompanying drawing explanation
The structural representation of Tu1Shi flexible robot manufacturing cell;
Fig. 2 is the extracting figure of the dispatching method of a kind of flexible robot manufacturing cell provided by the present invention;
Fig. 3 is the implementing procedure figure of the dispatching method of a kind of flexible robot manufacturing cell provided by the present invention.
Embodiment
Specifically illustrate embodiments of the present invention below in conjunction with accompanying drawing, accompanying drawing is only for reference and use is described, does not form the restriction to scope of patent protection of the present invention.
The dispatching method of a kind of flexible robot manufacturing cell provided by the present invention, comprises the following steps:
A. according to the feature of robot building unit (as shown in Figure 1, mainly for features such as the multiple stage machining tool under different layout/workstation M1-M4, transfer robot, loading depot, discharge points) and manufacturing procedure founding mathematical models and extracting figure model (as shown in Figure 2), that determines the objective function of optimizing scheduling and Optimized Operation solves scope, using the inverse of described target function value as fitness function, determine that changing completion date is most optimizing scheduling target;
B. as shown in Figure 3, in the present embodiment, application genetic algorithm carries out initialization to the initial population produced based on lathe coding, according to manufacturing procedure sequence, insert robot carrying operation, and the individuality in described population is evaluated, that is: individual adaptive value gen is calculated, if individual fitness gen is not less than maximum algebraically, then Output rusults quitting a program, if individual fitness gen is less than maximum algebraically, then by roulette method choice population at individual, again through intersecting, mutation operator obtains colony of future generation, the genetic algorithm adopted in this step is three layer scheduling methods that heuristic carrying operation insertion and heuristic carrying task matching method combine,
C. according to the group coding that described genetic algorithm is determined, find out the critical path (critical path that gray shade part as shown in Figure 2 and arrow represent) of described extracting figure, and the lathe block found out in described critical path and robot block, by the relative position of manufacturing procedure in lathe block in mobile critical path, exchange the carrying operation in robot block in critical path, adjustment task matching builds search neighborhood, and search operation is carried out to localized mass field, calculate Maximal Makespan Cmax ', as shown in Figure 3, Maximal Makespan Cmax ' is compared with the Cmax containing the job-shop scheduling model carrying operation calculated, if Cmax ' is not more than Cmax, then retain original population and scheduling machine operation, if Cmax ' is greater than Cmax, then calculate adaptive value, upgrade original population, and record optimal result machine operation, relatively after Cmax ' and Cmax, adaptive value gen=gen+1, return the comparison step of adaptive value gen and maximum algebraically,
D. by the optimization to Maximal Makespan Cmax ', the optimum solution in critical path neighborhood is obtained.
In above-mentioned steps C, the rule that in mobile critical path, in lathe block, the relative position of manufacturing procedure is observed is: the aft-loaded airfoil that in lathe block, non-first manufacturing procedure is processed before moving to all manufacturing procedures or in lathe block, non-final one procedure moves to all manufacturing procedures, calculate the objective function of mobile rear gained each time, if it is more excellent, record;
In above-mentioned steps C, exchanging the rule that the carrying operation in critical path in robot block observes is: the carrying operation of robot block position respectively with the carrying operation transposition of its back location, calculate the objective function of gained after exchanging each time, if it is more excellent, record;
In above-mentioned steps C, adjustment task matching observes the heuristic rule that adjacent carrying operation distributes to different machines people, calculates the objective function of the rear gained of adjustment each time, if it is more excellent, and record;
The hybrid algorithm that the dispatching method application genetic algorithm of a kind of flexible robot manufacturing cell provided by the present invention combines with field searching algorithm determines the shortest completion date, the convenient scheduling to flexible robot, effectively improves production efficiency and saves production cost.
Above disclosedly be only preferred embodiment of the present invention, the scope of the present invention can not be limited with this, therefore according to the equivalent variations that the present patent application the scope of the claims is done, still belong to the scope that the present invention is contained.
Claims (5)
1. a dispatching method for flexible robot manufacturing cell, is characterized in that, comprises the following steps:
A. according to the feature of robot building unit and manufacturing procedure founding mathematical models and extracting figure model, that determines the objective function of optimizing scheduling and Optimized Operation solves scope, using the inverse of described target function value as fitness function, determine that minimizing completion date is optimizing scheduling target;
B. apply genetic algorithm initialization population, and the individuality in described population is evaluated, obtain colony of future generation through selection, intersection, mutation operator;
C. according to the group coding that described genetic algorithm is determined, find out the critical path of described extracting figure, and the lathe block found out in described critical path and robot block, by the relative position of manufacturing procedure in lathe block in mobile critical path, exchange carrying operation in critical path in robot block, adjustment task matching builds search neighborhood;
D. the optimum solution in critical path neighborhood is obtained.
2. the dispatching method of flexible robot manufacturing cell according to claim 1, is characterized in that:
The genetic algorithm adopted in described step B is three layer scheduling methods that heuristic carrying operation insertion and heuristic carrying task matching method combine.
3. the dispatching method of flexible robot manufacturing cell according to claim 1, is characterized in that:
The rule that in mobile critical path in step C, in lathe block, the relative position of manufacturing procedure is observed is:
The aft-loaded airfoil that in lathe block, non-first manufacturing procedure is processed before moving to all manufacturing procedures or in lathe block, non-final one procedure moves to all manufacturing procedures, calculates the objective function of mobile rear gained each time, if it is more excellent, and record.
4. the dispatching method of flexible robot manufacturing cell according to claim 1, is characterized in that:
The rule that carrying operation in exchange critical path in step C in robot block is observed is:
The carrying operation of robot block position respectively with the carrying operation transposition of its back location, calculate the objective function of gained after exchanging each time, if it is more excellent, record.
5. the dispatching method of flexible robot manufacturing cell according to claim 1, is characterized in that:
Adjustment task matching in step C observes the heuristic rule that adjacent carrying operation distributes to different machines people, calculates the objective function of the rear gained of adjustment each time, if it is more excellent, and record.
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106651086A (en) * | 2016-09-07 | 2017-05-10 | 河南科技学院 | Automated stereoscopic warehouse scheduling method considering assembling process |
| CN106933200A (en) * | 2015-12-31 | 2017-07-07 | 中国科学院沈阳计算技术研究所有限公司 | The control method of the solution Flexible Job-shop Scheduling Problems based on genetic algorithm |
| CN109116816A (en) * | 2018-07-25 | 2019-01-01 | 昆明理工大学 | The Optimization Scheduling of printing process under a kind of Flexible Manufacture environment |
| CN109213080A (en) * | 2017-06-29 | 2019-01-15 | 深圳模德宝科技有限公司 | A kind of control method and its device of lathe |
| CN109242357A (en) * | 2018-10-25 | 2019-01-18 | 广州中浩控制技术有限公司 | A kind of process edit methods of MES system |
| CN109409774A (en) * | 2018-11-14 | 2019-03-01 | 合肥工业大学智能制造技术研究院 | Dispatching method, system and storage medium for intelligence manufacture digitlization workshop |
| CN112330221A (en) * | 2020-11-30 | 2021-02-05 | 华中科技大学 | Job shop scheduling optimization method with sufficient necessary condition neighborhood structure |
| CN112975427A (en) * | 2021-03-09 | 2021-06-18 | 扬州哈工科创机器人研究院有限公司 | Electric automation system for chuck production |
| CN113592203A (en) * | 2021-09-28 | 2021-11-02 | 武汉飞恩微电子有限公司 | Intelligent optimization method and system for production operation scheduling of pressure sensor |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101216710A (en) * | 2007-12-28 | 2008-07-09 | 东南大学 | Self-adapting selection dynamic production scheduling control system accomplished through computer |
| US8606386B2 (en) * | 2010-03-12 | 2013-12-10 | Ana Maria Dias Medureira Pereira | Multi-agent system for distributed manufacturing scheduling with Genetic Algorithms and Tabu Search |
| CN103592920A (en) * | 2013-11-19 | 2014-02-19 | 天津工业大学 | Hybrid flow shop scheduling method with finite buffers |
| CN103838219A (en) * | 2013-09-09 | 2014-06-04 | 昆明理工大学 | Optimized dispatching method of photosensitive resistance welding process in multilayer printed circuit board manufacturing |
-
2015
- 2015-04-20 CN CN201510187503.9A patent/CN104808629B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101216710A (en) * | 2007-12-28 | 2008-07-09 | 东南大学 | Self-adapting selection dynamic production scheduling control system accomplished through computer |
| US8606386B2 (en) * | 2010-03-12 | 2013-12-10 | Ana Maria Dias Medureira Pereira | Multi-agent system for distributed manufacturing scheduling with Genetic Algorithms and Tabu Search |
| CN103838219A (en) * | 2013-09-09 | 2014-06-04 | 昆明理工大学 | Optimized dispatching method of photosensitive resistance welding process in multilayer printed circuit board manufacturing |
| CN103592920A (en) * | 2013-11-19 | 2014-02-19 | 天津工业大学 | Hybrid flow shop scheduling method with finite buffers |
Non-Patent Citations (1)
| Title |
|---|
| 陶宇: "《Job_shop类型机器人制造单元调度问题与算法研究》", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106933200A (en) * | 2015-12-31 | 2017-07-07 | 中国科学院沈阳计算技术研究所有限公司 | The control method of the solution Flexible Job-shop Scheduling Problems based on genetic algorithm |
| CN106651086A (en) * | 2016-09-07 | 2017-05-10 | 河南科技学院 | Automated stereoscopic warehouse scheduling method considering assembling process |
| CN109213080A (en) * | 2017-06-29 | 2019-01-15 | 深圳模德宝科技有限公司 | A kind of control method and its device of lathe |
| CN109116816A (en) * | 2018-07-25 | 2019-01-01 | 昆明理工大学 | The Optimization Scheduling of printing process under a kind of Flexible Manufacture environment |
| CN109242357A (en) * | 2018-10-25 | 2019-01-18 | 广州中浩控制技术有限公司 | A kind of process edit methods of MES system |
| CN109242357B (en) * | 2018-10-25 | 2021-05-11 | 广州中浩控制技术有限公司 | Process editing method of MES system |
| CN109409774A (en) * | 2018-11-14 | 2019-03-01 | 合肥工业大学智能制造技术研究院 | Dispatching method, system and storage medium for intelligence manufacture digitlization workshop |
| CN112330221A (en) * | 2020-11-30 | 2021-02-05 | 华中科技大学 | Job shop scheduling optimization method with sufficient necessary condition neighborhood structure |
| CN112975427A (en) * | 2021-03-09 | 2021-06-18 | 扬州哈工科创机器人研究院有限公司 | Electric automation system for chuck production |
| CN113592203A (en) * | 2021-09-28 | 2021-11-02 | 武汉飞恩微电子有限公司 | Intelligent optimization method and system for production operation scheduling of pressure sensor |
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