CN105787229A - Joint optimization method for design and running of automatic production line - Google Patents
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Abstract
The invention relates to a joint optimization method for design and running of an automatic production line. The joint optimization method comprises the following steps: S1) acquiring the design requirement information of the production line; S2) performing preliminary layout planning on the production line; S3) designing a simulation model and an algorithm engine of the production line; S4) establishing an instruction channel and establishing an information channel; S5) receiving input sample information and generating a production instruction, running according to the production instruction and generating the running result into on-site information by the simulation model and feeding back the running result to the algorithm engine; S6) analyzing the running result of the simulation model, optimizing the algorithm engine and/or simulation model according to the analysis result and then executing the step S5 till meeting a first preset condition and then quitting; and S7) judging if the layout plan meets a second preset condition, if yes, outputting a layout scheme of the production line and/or intelligently executing the kernel; and if not, adjusting the layout plan and executing the step S3.
Description
Technical field
The invention belongs to technical field of automation in industry, be specifically related to the design of a kind of automatic production line and the method running combined optimization layout.
Background technology
In order to promote industrialization and intelligent fusion, industry 4.0 is advanced to build, it is necessary to accelerate the whole line construction of production of propelling Different Industries intellectually and automatically.Along with the fast development of computer, intelligent manufacturing equipment and communication technology, the whole line of automated production is quickly designed by China's manufacturing industry and the demand of reasonable implementation is day by day urgent, and how making the whole line of production design quickly rationally also can Effec-tive Function.The whole line of production of intellectually and automatically is by integrated multiple automation equipments, makes to realize between each equipment information and physical communication, and can carry out intelligentized command scheduling on upper strata.The whole line energy Improving The Quality of Products of automated production, raising production efficiency and minimizing recruitment number etc., the whole line of automated production has strong customized demand and industry dependency, special plane equipment and technology is closely related, intermediate equipment depends in the processing form of goods and physical property, and whole line equipment must is fulfilled for plant layout's demand and the expection production capacity demand of personalization.How quickly designing the whole line that produces configuring rationally, running efficient intellectually and automatically is a pendulum difficult problem in face of manufacturing enterprise.
Fig. 1 is traditional design method flow chart, whole line design is carried out according to mathematical analysis and experience typically via planning and designing personnel, designer's experience is had relatively strong dependency, and the Mathematical Models of foundation is on the basis that part is assumed, it is impossible to fully react practical problem.Go into operation in the complicated manufacture system run outside Present Domestic, up to 60% because initial stage planning is unreasonable or slips up and causes the index being not reaching to design in advance.Application along with the development of computer technology and Virtual Simulation, the planning and designing that virtual emulation design carries out production line by emulation platform become a kind of feasible and effective method: first in a traditional way production line is carried out initial designs, then emulation platform is being relied on to be modeled, and whether carry out its design of simulating, verifying in simulation software to designing a model reasonable, find out design problem that may be present, it is designed the optimization of scheme again, in order to determine final design scheme.The design of existing virtual emulation can utilize computer virtual simulation technical modelling to go out production line three-dimensional layout in future and running status compared with traditional design method, and its reasonability can be verified in advance, it is possible to quickly realize the important research instrument of automatic Production Line and planning.But whole line automation system typical case's discrete event often manufactures system, it is in large scale and structure is complicated, there is numerous random factor, be planned for actual motion from the initial stage and all there is the decision problem of complexity, and Multiple Attribute Decision Problems is widely present the various aspects of production.Manufacturing System Design and optimization process are difficult to clearly determine destination object, and object function is difficult to solve in conventional resolution mode so that design and enforcement are all extremely difficult to expected effect.Can organically being combined according to actual operation logic by the relevant factor of system by simulation modeling, truly reflect the behavior of system, but phantom is only the directviewing description to problem, simulation run can only provide the feasible program under certain condition.
Therefore, the present invention proposes design and the operation combined optimization method of a kind of automatic production line based on emulation.
Summary of the invention
It is contemplated that at least solve one of technical problem of existence in prior art.For this, the present invention proposes design and the operation combined optimization method of a kind of automatic production line, and the method has the experience that need not highly rely on designer, efficiently finds the optimization layout of production line rapidly.
In order to realize object above, the invention provides the design of a kind of automatic production line and run combined optimization method, the method includes: step S1, obtains the designing requirement information of described production line；Step S2, does preliminary allocation plan according to described designing requirement information to described production line；Step S3, designs phantom and the algorithm engine of described production line according to described allocation plan；Step S4, sets up the described algorithm engine instruction path to described phantom, sets up the described phantom communication channel to described algorithm engine, so that described phantom and described algorithm engine realize mutual；Step S5, receives the sample information of input, and described algorithm engine generates production ordering after performing, and described phantom runs according to described production ordering, and operation result generation field data is fed back to described algorithm engine；Step S6, is analyzed the operation result of described phantom, algorithm engine and/or phantom according to described analysis result optimizing, then performs step S5, until meeting the first pre-conditioned backed off after random；Step S7, it is judged that whether described placement scheme meets second pre-conditioned, meets, then the placement scheme and/or the intelligence that export described production line perform kernel；It is unsatisfactory for, then adjusts allocation plan, perform step S3.
Mutual due to what establish between simulation model and algorithm engine, the production line mode of production of optimum is looked for by interactive iteration between the two, with traditional simply by compared with being manually entered the analogy method carrying out simple production line, it is possible to compensate for the defect that designer lacks experience largely；By adjustment allocation plan repeatedly, it is possible to search out the layout method adapted with production line rapidly efficiently.It should be noted that above-mentioned second pre-conditioned itself can also be a pre-conditioned set, each condition for pre-conditioned set the inside can export a placement scheme meeting this condition and/or intelligence performs kernel, that is list can export optimal solution, near-optimum solution can also be exported, thus greatly facilitated designer's selection to placement scheme.
According to one embodiment of present invention, before performing above-mentioned steps S2, it is preset with the placement model corresponding with described production line industry, different placement models can be selected according to described designing requirement information, described production line is done preliminary allocation plan on the basis of described placement model.
It is preset with the placement model (part mainly for production line general character) corresponding with production line industry, so can reduce the work of designer's repeatability, also reduce the probability made mistakes simultaneously, improve the time of modeling.
According to one embodiment of present invention, the phantom designing described production line includes: step S3.1, and the equipment of described production line is carried out three-dimensional modeling；Step S3.2, it is determined that moving part in described model and not moving part, and set the motion mode of described moving part；Step S3.3, sets up the control mode of described model, wherein, including collection and the process of data, sensor layout, control the setting of logic；Step S3.4, assembles described model according to described preliminary allocation plan.
According to another embodiment of the invention, the algorithm engine designing described production line includes: step S4.1, and the model of described production line is carried out mathematical modeling；Step S4.2, carries out mathematical modeling to the motor process of described moving part；Step S4.3, formulates optimized algorithm according to the mathematical model set up；Step S4.4, according to the formulation and implementation of described production line and the algorithm engine dispatching described optimized algorithm.
Different with traditional method, the operation of the model of production line is also configured with algorithm engine by the present invention, by algorithm engine running optimizatin algorithm, thus reaching to make the purpose of the arrangement of model and optimizing operating mode.
It is possible to further carry out cluster analysis according to the degree of coupling between model, thus model partition is become multiple Model Group, and formulate the optimized algorithm corresponding with Model Group.
By first model being carried out cluster analysis, become multiple Model Group to formulate optimized algorithm model partition, so can find more excellent placement scheme quickly.
An alternative embodiment of the invention discloses the concrete interactive mode between simulation model and algorithm engine.Receiving the sample information of input, described algorithm engine generates production ordering after performing and is stored in instruction database, and described phantom accepts corresponding instruction in real time in described instruction database, and performs respective action；The field data collecting phantom is stored in field data data base, after carrying out state analysis, feeds back to described algorithm engine.
By being provided with intermediate database, i.e. instruction database and field data data base, be so conducive to back looking into, find abnormal data point, be more beneficial for optimized algorithm engine and phantom.
An alternative embodiment of the invention discloses concrete optimization object, and algorithm engine according to described analysis result optimizing includes the algorithm structure optimizing this algorithm engine；Phantom according to described analysis result optimizing includes the configuration parameter optimizing this phantom.
According to one embodiment of present invention, described first pre-conditioned includes: make the optimization that described algorithm engine and phantom reach balance-type.
According to one embodiment of present invention, described second pre-conditioned includes: described production line carries out adaptability and analysis on its rationality, and makes comparisons with pre-set level parameter analyzing a result.
The additional aspect of the present invention and advantage will part provide in the following description, and part will become apparent from the description below, or is recognized by the practice of the present invention.
Accompanying drawing explanation
Fig. 1 is traditional design method flow chart；
Fig. 2 is the Outline Design figure of method for designing of the present invention；
Fig. 3 is the detailed design figure of method for designing of the present invention.
Detailed description of the invention
Being described below in detail embodiments of the invention, the example of described embodiment is shown in the drawings, and wherein same or similar label represents same or similar element or has the element of same or like function from start to finish.The embodiment described below with reference to accompanying drawing is illustrative of, it is intended to is used for explaining the present invention, and is not considered as limiting the invention.
Following disclosure provides many different embodiments or example for realizing the different structure of the present invention.In order to simplify disclosure of the invention, hereinafter parts and setting to specific examples are described.Certainly, they are only merely illustrative, and are not intended to the restriction present invention.Additionally, the present invention can in different examples repeat reference numerals and/or letter.This repetition is for purposes of simplicity and clarity, the relation between itself not indicating discussed various embodiment and/or arranging.Additionally, the example of the various specific technique that the invention provides and material, but those of ordinary skill in the art are it can be appreciated that the use of the property of can be applicable to of other techniques and/or other materials.
As shown in Figure 2,3, the design of a kind of automatic production line with run combined optimization method, the method is mainly supported whole production line quickly to design and performs iteration optimization, and described method specifically comprises the following steps that
S1 walks: whole line designing requirement information data obtains, and investigates the product of production line processing and determines its processing technique path；Investigate the process equipment of each working procedure processing needs and the productive temp of this operation；Investigate the specifying information of this factory's actual field space, ground and existing equipment；Investigation this production line of factory planning requires the production capacity etc. reached.Needs obtain information in detailed below: capacity requirements, factory floor, work flow, productive temp, the production schedule, Process Plans, process equipment etc.；
S2 walks: initial whole line allocation plan, tentatively quickly several Production Line Configureds mode is alternatively determined according to investigation information, or it is analyzed summing up according to several layout type that existing row is commonly used in the trade, determine the whole line preliminary placement conceptual design of production, including device resource configuration, whole line layout and processing route planning etc..1) resource distribution: the equipment of each process section needs and quantity thereof；2) processing route planning: according to the processing route of product, it is determined that the standard work force in each operation, the process equipment analyzing each technique of product corresponding associates with the technique of operation；3) whole line layout: the production capacity reached according to the factory floor space of enterprise, Product processing operation and hope, carries out rational space layout, physical interference analysis and logistics route planning, it is determined that whole line layout to existing equipment, intermediate equipment and the plan equipment of coming into operation.
The placement model corresponding with production line industry can be preset with, different placement model'ss (such as In-put design requires the placement model that information Auto-matching is different) can be selected, described production line is done preliminary allocation plan on the basis of described placement model according to designing requirement information.So can reduce the dependence to designer, reduce basic makeing mistakes, improve the efficiency of layout.
S3 walks: whole line static state custom design, including whole line simulation model design and the design of whole line algorithm engine.
1) whole line simulation model design:
First, the threedimensional model of all devices is set up according to preliminary whole line allocation plan；Secondly, it is determined that moving part in model and not moving part, the motion mode of moving part has been planned；Then, the control program of whole line is designed, including collection and the process of data, the layout of sensor, control logical design etc.；Finally, in simulation software, whole line layout and assembling are carried out according to whole line allocation plan.
2) whole line algorithm engine design:
First, according to preliminary whole line allocation plan, whole line is carried out mathematical modeling；Secondly, its motor process is carried out mathematical modeling；Then, according to the mathematical model that each unit module is set up, the intelligent optimization algorithm of the module that research and development are corresponding solves；Finally, research and develop whole line and perform and dispatching algorithm engine, as the kernel of whole line production system.
S4, S5 walk: set up the described algorithm engine instruction path to described phantom, set up the described phantom communication channel to described algorithm engine, so that described phantom and described algorithm engine realize mutual.Whole line intelligence performs, refer mainly to pass through when phantom runs the dynamic interaction of instruction transmission and data acquisition realization " instruction is descending " with " information upstream " with algorithm engine, simulation result is analyzed by Dynamic Execution process, the optimized algorithm in update algorithm engine and/or the configuration parameter in phantom.
1) instruction is descending, it is simulated in simulation software by inputting sample information (such as sample sequence information), sample order is converted into production ordering by algorithm enforcement engine, it is stored in instruction database, according to the corresponding instruction of acceptance in instruction database that the control program in model is real-time with Lower level logical during simulation run, and perform respective action；
2) information upstream, by collecting the field data of the sensor Real-time Collection of layout at phantom, after carrying out state analysis, feeds back to algorithm enforcement engine equipment instantaneous operating conditions.
S6 walks: " design-run " Joint iteration optimization, the optimized algorithm of algorithm engine is performed by iterative the configuration parameter adjusting Static Design and intelligence, making whole line simulation model and algorithm engine reach the optimization of balance-type, the optimization of balance-type here can make the cooperation of phantom and algorithm engine reach the peak of production efficiency；After meeting first pre-conditioned (reaching the optimization of balance-type), exit the iteration between S5 and S6 and run, down perform S7 step.
S7 walks: the effect that whole line dynamic and intelligent is performed carries out statistical analysis, including Adaptability Analysis, analysis on its rationality etc., make comparisons with pre-set level parameter analyzing result, see and whether meet requirement, satisfied then export whole line design and intelligence perform kernel, it is unsatisfactory for, then improves whole line layout design scheme, re-execute S3 step.By design iterate with combining of performing (operations) optimize after be possible not only to obtain the whole line design of a kind of optimum, while can form whole line intelligence execution kernel.
Owing to needing the algorithm structure of configuration parameter and the algorithm engine adjusting phantom iteratively, the layout of the best is found again on this basis, operand and resource requirement to system are very big, occupy this, the invention allows for a kind of method reducing system operations amount.The method is exactly after being modeled phantom, cluster analysis is carried out according to the degree of coupling between model, thus model is divided into multiple Model Group, reenact the optimized algorithm corresponding with Model Group, production line is thus equivalent to divide into many sub-production lines according to the size of the degree of coupling, the allocation plan of antithetical phrase production line is made to optimize, owing to doing computing just for sub-production line, operand then can be greatly reduced, and all right concurrent operation between each sub-production line, greatly reduce the time of computing.
In describing the invention, it will be appreciated that, term " " center ", " length ", " width ", " thickness ", " on ", D score, " front ", " afterwards ", " left side ", " right side ", " vertically ", " level ", " top ", " end ", " interior ", " outward ", " axially ", " radially ", orientation or the position relationship of the instruction such as " circumference " are based on orientation shown in the drawings or position relationship, it is for only for ease of the description present invention and simplifies description, rather than the device of instruction or hint indication or element must have specific orientation, with specific azimuth configuration and operation, therefore it is not considered as limiting the invention.
Additionally, term " first ", " second " are only for descriptive purposes, and it is not intended that indicate or imply relative importance or the implicit quantity indicating indicated technical characteristic.Thus, define " first ", the feature of " second " can express or implicitly include one or more these features.In describing the invention, " multiple " are meant that two or more, unless otherwise expressly limited specifically.
In the present invention, unless otherwise clearly defined and limited, the term such as term " installation ", " being connected ", " connection ", " fixing " should be interpreted broadly, for instance, it is possible to it is fixing connection, it is also possible to be removably connect, or integral；Can be mechanically connected, it is also possible to be electrical connection, it is also possible to be communication；Can be joined directly together, it is also possible to be indirectly connected to by intermediary, it is possible to be connection or the interaction relationship of two elements of two element internals.For the ordinary skill in the art, it is possible to understand above-mentioned term concrete meaning in the present invention as the case may be.
In the present invention, unless otherwise clearly defined and limited, fisrt feature second feature " on " or D score can be that the first and second features directly contact, or the first and second features are by intermediary mediate contact.And, fisrt feature second feature " on ", " top " and " above " but fisrt feature directly over second feature or oblique upper, or be merely representative of fisrt feature level height higher than second feature.Fisrt feature second feature " under ", " lower section " and " below " can be fisrt feature immediately below second feature or obliquely downward, or be merely representative of fisrt feature level height less than second feature.
In the description of this specification, specific features, structure, material or feature that the description of reference term " embodiment ", " some embodiments ", " example ", " concrete example " or " some examples " etc. means in conjunction with this embodiment or example describe are contained at least one embodiment or the example of the present invention.In this manual, the schematic representation of above-mentioned term is necessarily directed to identical embodiment or example.And, the specific features of description, structure, material or feature can combine in one or more embodiments in office or example in an appropriate manner.Additionally, when not conflicting, the feature of the different embodiments described in this specification or example and different embodiment or example can be carried out combining and combining by those skilled in the art.
The know-why of the present invention is described above in association with specific embodiment.These descriptions are intended merely to explanation principles of the invention, and can not be construed to limiting the scope of the invention by any way.Based on explanation herein, those skilled in the art need not pay performing creative labour can associate other detailed description of the invention of the present invention, and these modes fall within protection scope of the present invention.
Claims (9)
1. the design of an automatic production line and operation combined optimization method, it is characterised in that including:
Step S1, obtains the designing requirement information of described production line；
Step S2, does preliminary allocation plan according to described designing requirement information to described production line；
Step S3, designs phantom and the algorithm engine of described production line according to described allocation plan；
Step S4, sets up the described algorithm engine instruction path to described phantom, sets up the described phantom communication channel to described algorithm engine, so that described phantom and described algorithm engine realize mutual；
Step S5, receives the sample information of input, and described algorithm engine generates production ordering after performing, and described phantom runs according to described production ordering, and operation result generation field data is fed back to described algorithm engine；
Step S6, is analyzed the operation result of described phantom, algorithm engine and/or phantom according to described analysis result optimizing, then performs step S5, until meeting the first pre-conditioned backed off after random；
Step S7, it is judged that whether described placement scheme meets second pre-conditioned, meets, then the placement scheme and/or the intelligence that export described production line perform kernel；It is unsatisfactory for, then adjusts allocation plan, perform step S3.
2. the design of automatic production line according to claim 1 and operation combined optimization method, it is characterised in that
Before performing described step S2, it is preset with the placement model corresponding with described production line industry, different placement models can be selected according to described designing requirement information, described production line is done preliminary allocation plan on the basis of described placement model.
3. the design of automatic production line according to claim 1 and operation combined optimization method, it is characterised in that the phantom designing described production line includes:
Step S3.1, carries out three-dimensional modeling to the equipment of described production line；
Step S3.2, it is determined that moving part in model and not moving part, and set the motion mode of described moving part；
Step S3.3, sets up the control mode of described model, wherein, including collection and the process of data, sensor layout, control the setting of logic；
Step S3.4, assembles described model according to described preliminary allocation plan.
4. the design of automatic production line according to claim 3 and operation combined optimization method, it is characterised in that the algorithm engine designing described production line includes:
Step S4.1, carries out mathematical modeling to the model of described production line；
Step S4.2, carries out mathematical modeling to the motor process of described moving part；
Step S4.3, formulates optimized algorithm according to the mathematical model set up；
Step S4.4, according to the formulation and implementation of described production line and the algorithm engine dispatching described optimized algorithm.
5. according to the design of the automatic production line described in claim 4 and operation combined optimization method, it is characterised in that
Carry out cluster analysis according to the degree of coupling between described model, so that described model partition is become multiple Model Group, and formulate the optimized algorithm corresponding with described Model Group.
6. the design of automatic production line according to claim 1 and operation combined optimization method, it is characterized in that, receive the sample information of input, described algorithm engine generates production ordering after performing and is stored in instruction database, described phantom accepts corresponding instruction in real time in described instruction database, and performs respective action；The field data collecting phantom is stored in field data data base, after carrying out state analysis, feeds back to described algorithm engine.
7. the design of automatic production line according to claim 1 and operation combined optimization method, it is characterised in that algorithm engine according to described analysis result optimizing includes the algorithm structure optimizing described algorithm engine；Phantom according to described analysis result optimizing includes the configuration parameter optimizing described phantom.
8. the design of automatic production line according to claim 1 with run combined optimization method, it is characterised in that described first pre-conditioned includes: make the optimization that described algorithm engine and phantom reach balance-type.
9. the design of automatic production line according to claim 1 with run combined optimization method, it is characterised in that described second pre-conditioned includes: described production line carries out adaptability and analysis on its rationality, and makes comparisons with pre-set level parameter analyzing a result.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106563776A (en) * | 2016-10-28 | 2017-04-19 | 宁夏共享模具有限公司 | Control system and control method of casting shaping process |
| CN107862110A (en) * | 2017-10-17 | 2018-03-30 | 广东工业大学 | A kind of electronic product assembly line virtually changes production method |
| CN107885581A (en) * | 2017-11-24 | 2018-04-06 | 广东惠利普路桥信息工程有限公司 | A kind of shop-floor management simulation system and its method |
| CN109102187A (en) * | 2018-08-09 | 2018-12-28 | 广东工业大学 | A kind of virtual thread-changing method of configuration parameter input and scheme visualization output |
| WO2019076233A1 (en) * | 2017-10-17 | 2019-04-25 | 广东工业大学 | Quick customization design method and system for intelligent workshop |
| CN112508489A (en) * | 2020-12-16 | 2021-03-16 | 北京航天智造科技发展有限公司 | Top-level planning design method for complex equipment manufacturing |
| WO2021237748A1 (en) * | 2020-05-29 | 2021-12-02 | 西门子（中国）有限公司 | Production line planning method and device thereof |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104077630A (en) * | 2014-05-26 | 2014-10-01 | 浙江工业大学 | Workshop layout method for complex job of simulating human cell evolution |
| CN104091027A (en) * | 2014-07-17 | 2014-10-08 | 中国科学院自动化研究所 | Visual workshop layout optimization method and system |
-
2016
- 2016-05-23 CN CN201610342540.7A patent/CN105787229B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104077630A (en) * | 2014-05-26 | 2014-10-01 | 浙江工业大学 | Workshop layout method for complex job of simulating human cell evolution |
| CN104091027A (en) * | 2014-07-17 | 2014-10-08 | 中国科学院自动化研究所 | Visual workshop layout optimization method and system |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106563776A (en) * | 2016-10-28 | 2017-04-19 | 宁夏共享模具有限公司 | Control system and control method of casting shaping process |
| CN107862110A (en) * | 2017-10-17 | 2018-03-30 | 广东工业大学 | A kind of electronic product assembly line virtually changes production method |
| WO2019076231A1 (en) * | 2017-10-17 | 2019-04-25 | 广东工业大学 | Virtual product switching method for electronic product production line |
| WO2019076233A1 (en) * | 2017-10-17 | 2019-04-25 | 广东工业大学 | Quick customization design method and system for intelligent workshop |
| JP2020521251A (en) * | 2017-10-17 | 2020-07-16 | 広東工業大学Ｇｕａｎｇｄｏｎｇ Ｕｎｉｖｅｒｓｉｔｙ Ｏｆ Ｔｅｃｈｎｏｌｏｇｙ | Virtual product change method of electronic product production line |
| US10915096B2 (en) | 2017-10-17 | 2021-02-09 | Guangdong University Of Technology | Method and system for quick customized-design of intelligent workshop |
| CN107885581A (en) * | 2017-11-24 | 2018-04-06 | 广东惠利普路桥信息工程有限公司 | A kind of shop-floor management simulation system and its method |
| CN109102187A (en) * | 2018-08-09 | 2018-12-28 | 广东工业大学 | A kind of virtual thread-changing method of configuration parameter input and scheme visualization output |
| WO2021237748A1 (en) * | 2020-05-29 | 2021-12-02 | 西门子（中国）有限公司 | Production line planning method and device thereof |
| CN112508489A (en) * | 2020-12-16 | 2021-03-16 | 北京航天智造科技发展有限公司 | Top-level planning design method for complex equipment manufacturing |
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