CN109032538A - Application method of the big data in 3D printing technique - Google Patents
Application method of the big data in 3D printing technique Download PDFInfo
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- CN109032538A CN109032538A CN201710438777.XA CN201710438777A CN109032538A CN 109032538 A CN109032538 A CN 109032538A CN 201710438777 A CN201710438777 A CN 201710438777A CN 109032538 A CN109032538 A CN 109032538A
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- 238000000034 method Methods 0.000 title claims abstract description 57
- 238000010146 3D printing Methods 0.000 title claims abstract description 22
- 238000007639 printing Methods 0.000 claims abstract description 40
- 239000000463 material Substances 0.000 claims abstract description 18
- 238000012545 processing Methods 0.000 claims abstract description 12
- 238000004220 aggregation Methods 0.000 claims abstract description 8
- 230000002776 aggregation Effects 0.000 claims abstract description 8
- 238000007405 data analysis Methods 0.000 claims abstract description 7
- 238000010438 heat treatment Methods 0.000 claims abstract description 5
- 230000001105 regulatory effect Effects 0.000 claims abstract description 3
- 238000004422 calculation algorithm Methods 0.000 claims description 15
- 230000002068 genetic effect Effects 0.000 claims description 9
- 238000004364 calculation method Methods 0.000 claims description 4
- 238000010884 ion-beam technique Methods 0.000 claims description 4
- 239000012141 concentrate Substances 0.000 claims description 3
- 238000010894 electron beam technology Methods 0.000 claims description 3
- 238000003860 storage Methods 0.000 claims description 3
- 230000001960 triggered effect Effects 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 description 17
- 239000000047 product Substances 0.000 description 14
- 230000008569 process Effects 0.000 description 8
- 238000005516 engineering process Methods 0.000 description 7
- 239000000843 powder Substances 0.000 description 6
- 238000005245 sintering Methods 0.000 description 5
- 230000000694 effects Effects 0.000 description 3
- 230000004927 fusion Effects 0.000 description 3
- 239000007787 solid Substances 0.000 description 3
- 238000010009 beating Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 239000013067 intermediate product Substances 0.000 description 2
- 238000003892 spreading Methods 0.000 description 2
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- 238000012360 testing method Methods 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000004888 barrier function Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000012824 chemical production Methods 0.000 description 1
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/12—Digital output to print unit, e.g. line printer, chain printer
- G06F3/1201—Dedicated interfaces to print systems
- G06F3/1202—Dedicated interfaces to print systems specifically adapted to achieve a particular effect
- G06F3/1203—Improving or facilitating administration, e.g. print management
- G06F3/1204—Improving or facilitating administration, e.g. print management resulting in reduced user or operator actions, e.g. presetting, automatic actions, using hardware token storing data
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B33—ADDITIVE MANUFACTURING TECHNOLOGY
- B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
- B33Y50/00—Data acquisition or data processing for additive manufacturing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/12—Digital output to print unit, e.g. line printer, chain printer
- G06F3/1201—Dedicated interfaces to print systems
- G06F3/1223—Dedicated interfaces to print systems specifically adapted to use a particular technique
- G06F3/1224—Client or server resources management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/12—Digital output to print unit, e.g. line printer, chain printer
- G06F3/1201—Dedicated interfaces to print systems
- G06F3/1223—Dedicated interfaces to print systems specifically adapted to use a particular technique
- G06F3/1237—Print job management
- G06F3/1253—Configuration of print job parameters, e.g. using UI at the client
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/12—Digital output to print unit, e.g. line printer, chain printer
- G06F3/1201—Dedicated interfaces to print systems
- G06F3/1278—Dedicated interfaces to print systems specifically adapted to adopt a particular infrastructure
- G06F3/1285—Remote printer device, e.g. being remote from client or server
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
- G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
Abstract
The invention discloses a kind of application method of big data in 3D printing technique, the method uses the online print platform based on big data, the platform includes: printing device, server, client, the client connects the server, the server connects the printing device, and the client includes computer or mobile phone, and the server includes sequentially connected network module, data module, memory module, parsing module, aggregation module and application module；Described method includes following steps: 1) printing device is using high energy heat source according to setup parameter heating material；2) 3D printing demand and threedimensional model are passed to server by client；3) operating parameter is connect by internet with cloud server by server；4) parameter that cloud server sends step 3) carries out big data analysis processing, and feeds back to server and regulated and controled；5) printing device receives server print command, is printed.
Description
Technical field
The invention belongs to chemical production technical fields, and in particular to a kind of application side of big data in 3D printing technique
Method.
Background technique
With the rise of big data technology, compared to traditional statistical method, big data more highlight only ask association, pay no attention to because
Fruit, the characteristics of focusing on the relevance between card analysis data, big data technology are complicated, implicit and be difficult to measure to factory is solved
Relationship is influenced between variable, has production status in its distinctive feature, such as production unit A to influence whether that unit A exports intermediate products
Quality, if the quality of intermediate products can not on-line testing or testing cost it is high, after these implicit relationships also will affect
The condition of production of continuous production unit B not only can be monitored and be diagnosed to the failure of unit A by big data analysis technology, and
And in time series, early warning can be carried out to the failure of production unit B, and remind operator to make and timely adjust.It is right
For Chemical Manufacture, very multi unit operation especially physical process has determining quality and energy balance relations, and process
Forward/backward operation unit be commonly present physical isolation, there is no correlation physically between physical parameter, directly adopt big data
Analytical technology, because existing noise effect between measurement data, or influenced by public work, these are not deposited physically
Usually occur the relevance of height on the model that big data is established in associated data, big data analysis personnel is allowed to be mistakenly considered
There are association, this association for violating physical law causes production technician to former so that the False Rate of fault diagnosis increases
Barrier detection generates distrust, brings certain resistance to propulsion industrial intelligent factory construction.
3D printing technique is the advanced manufacturing technology with Digitized manufacturing, highly flexible and adaptability, from 20
Century, late nineteen eighties were developed so far, oneself becomes a mainstay in modern advanced manufacturing technique.Precinct laser fusion skill
Art is one of the increases material manufacturing technology quickly grown in recent years, using dusty material as raw material, using laser to 3D solid
Section carries out successively scanning and completes raw basin, is not limited by part shape complexity, does not need any moulds of industrial equipment,
Have a wide range of application.The basic process of precinct laser fusion technique is: dust feeder send a certain amount of powder to work top, powdering
One layer of dusty material is laid in the upper surface of the molded part of piston by device, and galvanometer controls laser and takes turns according to the section of this layer
Exterior feature is scanned solid section powder bed, and the temperature of powder is made to rise to melting point, powder fusing sintering and with it is following molded
Part realize bonding；After a layer cross section has been sintered, workbench declines the thickness of a layer, and power spreading device is spread above again
One layer of uniformly densely powder carries out the scanning sintering of a new layer cross section, scans and be superimposed through several layers, until completing entire three-dimensional
Entity manufacture.In the process of running, workbench (i.e. by the bottom of the moulding cylinder of piston support) is general for precinct laser fusion equipment
Decline a thickness by motor driven, however since the precision of motor encoder is limited, so that obtained by calculation every time
Motor operates step number there is also fractional part, the prior art generally fractional part is used uniformly save, to integer into one or
The method to round up is handled, and in this way with the increase of the product sintering number of plies, error is also constantly adding up, therefore, with
Sintering product height is higher, and it is also bigger to accumulate existing error.Currently, also occurring operating step number to motor using absolute position
The mode positioned controls rising or falling for piston, although which can reduce the influence of accumulated error, motor
Positioning requires to calculate new locator value every time, i.e., requires to operate motor step number progress accumulation process every time, therefore, with
Product is sintered the increase of the number of plies, considerably increases the processing difficulty of data, and increases the biography of the data between upper and lower machine simultaneously
It is defeated, cause to be easy to appear mistake.
Summary of the invention
For above-mentioned technical problem of the existing technology, simple, the small big number of error is calculated the present invention provides a kind of
According to 3D printing application method, greatly reduce manufacturing procedure, shortens the process-cycle, improve the accuracy of manufacture of product, and product knot
Structure is more complicated, and the effect of manufacturing speed is more significant.
To realize above-mentioned technical problem, the invention adopts the following technical scheme:
A kind of application method of big data in 3D printing technique, the method are put down using the online printing based on big data
Platform, the platform include: printing device, server, client, the client connection server, the server company
The printing device is connect, the client includes computer or mobile phone, and the server includes sequentially connected network module, number
According to module, memory module, parsing module, aggregation module and application module；
The method specifically comprises the following steps:
1) printing device is using high energy heat source according to setup parameter heating material；
2) 3D printing demand and threedimensional model are passed to server by client；
3) operating parameter is connect by internet with cloud server by server；
4) parameter that cloud server sends step 3) carries out big data analysis processing, and feeds back to server and adjusted
Control；
5) printing device receives server print command, is printed.
Further, the server carries out printing device scheduling according to the dispatching algorithm based on genetic algorithm.
Further, the network module is built-in with 3G Internet device or WIFI Internet device；The network module is externally provided with
Multiple connecting pins USB.
Further, the parameter of the data module acquisition includes printing precision, stamp with the size, printed material and color, electricity
Machine operates step number, the revolution ratio of driving wheel and driven wheel.
Further, the memory module is flash memory type storage chip.
Further, the parsing module is used to parse the type of shaped article, carries out merger processing, by same section and
With one series of feature merger of triggering relationship between component.
Further, the aggregation module obtains the type and feature series of all over products, calculates the similarity between product,
And sorted out according to the similarity of the product.
Further, the application module, the classification for product provide the network service to match.
Further, high energy heat source is laser beam, electron beam, plasma or ion beam, the material in above method step 1)
Material is nonmetallic materials.
Further, the dispatching algorithm based on genetic algorithm the following steps are included:
(1) print request of client is after being uploaded to server, server timer-triggered scheduler, periodically counts newest printing and asks
It asks, concentrates the scheduling of task more, be convenient for changing and adjust, so that scheduling is more efficient and accurate.It is another
Aspect can reduce calculation amount, reduce system load；
(2) data structure for influencing printing device Scheduling factors is established, data structure includes that client requests class, printer class
With print out task class；It includes the location information of print request that the client, which requests class parameter,；The printer class parameter includes beating
Print the location information of request, printer completes the cost of printing, printer completes the time of printing；The print out task class parameter
Including completing, print out task is time-consuming, completes the overall cost printed, printer side at a distance from client；
(3) it is modeled based on genetic algorithm, i.e., it is a to m to be scheduled to beat when running up to n client request within a certain period of time
Printing apparatus carries out unified scheduling, which can be attributed to the optimal layout side that n tasks are completed in m platform machine
Case.
Application method of the big data of the present invention in 3D printing technique, by including the above-mentioned raising three-dimension object accuracy of manufacture
Detection platform avoid the prior art from making using pure mathematics mode so that procedure of processing is carried out according to big data calculated result
At error, overcome with product sintering the number of plies increase, increase data processing difficulty the drawbacks of, by the process of data processing
It moves in cloud server, greatly reduces the data handling requirements to 3D printing itself, reduce the manufacturing cost of 3D printing,
Simple with data processing, error is small, effect with high accuracy.
Detailed description of the invention
Fig. 1 is the flow diagram of application method of the big data of the present invention in 3D printing technique.
In figure: 1 client, 11 computers, 2 servers, 21 network modules, 22 data modules, 23 memory modules, 24 parsings
Module, 25 aggregation modules, 26 application modules, 3 printing devices
Specific embodiment
With reference to the accompanying drawing, the present invention is described in more detail.
The present invention provides a kind of application method of big data in 3D printing technique, and the method is used based on big data
Online print platform, the platform include: printing device, server, client, the client connection server, institute
It states server and connects the printing device, the client includes computer or mobile phone, and the server includes sequentially connected
Network module, data module, memory module, parsing module, aggregation module and application module；
The method specifically comprises the following steps:
1) printing device is using high energy heat source according to setup parameter heating material；
2) 3D printing demand and threedimensional model are passed to server by client；
3) operating parameter is connect by internet with cloud server by server；
4) parameter that cloud server sends step 3) carries out big data analysis processing, and feeds back to server and adjusted
Control；
5) printing device receives the print command of server, is printed.
The server carries out printing device scheduling according to the dispatching algorithm based on genetic algorithm.In the network module
It is equipped with 3G Internet device or WIFI Internet device；The network module is externally provided with multiple connecting pins USB.The data module acquisition
Parameter include printing precision, stamp with the size, printed material and color, motor operates step number, the revolution of driving wheel and driven wheel
Than.The memory module is flash memory type storage chip.The parsing module is used to parse the type of shaped article, carries out at merger
Reason will have one series of feature merger of triggering relationship between same section and component.The aggregation module obtains all
Type and the feature series of product, calculate the similarity between product, and sorted out according to the similarity of the product.Institute
Application module is stated, the classification for product provides the network service to match.High energy heat source is laser in above method step 1)
Beam, electron beam, plasma or ion beam, the material are nonmetallic materials.The dispatching algorithm based on genetic algorithm includes
Following steps:
(1) print request of client is after being uploaded to server, server timer-triggered scheduler, periodically counts newest printing and asks
It asks, concentrates the scheduling of task more, be convenient for changing and adjust, so that scheduling is more efficient and accurate.It is another
Aspect can reduce calculation amount, reduce system load；
(2) data structure for influencing printing device Scheduling factors is established, data structure includes that client requests class, printer class
With print out task class；It includes the location information of print request that the client, which requests class parameter,；The printer class parameter includes beating
Print the location information of request, printer completes the cost of printing, printer completes the time of printing；The print out task class parameter
Including completing, print out task is time-consuming, completes the overall cost printed, printer side at a distance from client；
(3) it is modeled based on genetic algorithm, i.e., it is a to m to be scheduled to beat when running up to n client request within a certain period of time
Printing apparatus carries out unified scheduling, which can be attributed to the optimal layout side that n tasks are completed in m platform machine
Case.
Application method of the big data in 3D printing technique accesses net by 3G Internet device or WIFI Internet device
Network is realized with cloud server and is connected to the network, reaches data transmission channel.It, can when needing to print article using 3D printer
3 D image file is accessed into network module by USB interface, cloud server, cloud server pair are sent to by network module
Data carry out parsing post-processing for the digital controlled signal of control printer work, then by the digital controlled signal by building
Network data transmission channel be sent to network module, network module send digital controlled signal to mechanical component and print head,
The work of the two is controlled, realizes three-dimensional printing,
Application method of the big data in 3D printing technique uses using laser melting process and is successively sintered and is superimposed
Method complete the overall process of entire 3D printing manufacture.That is, driving device drives power spreading device again after a layer cross section has been sintered
In layer overlay above, uniformly densely powder, the scanning for carrying out a new layer cross section are sintered, and superposition are scanned through several layers, until complete
It is manufactured at entire 3D solid.During 3D printing, 1) process equipment is using high energy heat source according to setup parameter heating material
It is allowed to that connecting shaping, 2) operating parameter in step 1) is connect by internet with cloud server by sensor, by dependency number
According to being sent to monitoring center；3) parameter that monitoring center sends step 2) carries out big data analysis processing, and to process equipment
Regulated and controled.
The purpose of the present invention, technical scheme and beneficial effects are described in detail above, it should be understood that the above institute
Only a specific embodiment of the invention is stated, is not intended to limit the scope of protection of the present invention, it is all in spirit of the invention
Any modification, equivalent substitution, improvement and etc. with being done within principle, should all be included in the protection scope of the present invention.
Claims (10)
1. a kind of application method of big data in 3D printing technique, the method be characterized in that using based on big data
Line print platform, the platform include: printing device, server, and client, the client connects the server, described
Server connects the printing device, and the client includes computer or mobile phone, and the server includes sequentially connected net
Network module, data module, memory module, parsing module, aggregation module and application module；
The method specifically comprises the following steps:
1) printing device is using high energy heat source according to setup parameter heating material；
2) 3D printing demand and threedimensional model are passed to server by client；
3) operating parameter is connect by internet with cloud server by server；
4) parameter that cloud server sends step 3) carries out big data analysis processing, and feeds back to server and regulated and controled；
5) printing device receives server print command, is printed.
2. method according to claim 1, which is characterized in that the server according to the dispatching algorithm based on genetic algorithm,
Carry out printing device scheduling.
3. method according to claim 1, which is characterized in that the network module is built-in with 3G Internet device or WIFI online
Device；The network module is externally provided with multiple connecting pins USB.
4. method according to claim 1, which is characterized in that the parameter of the data module acquisition includes that printing precision is beaten
Size, printed material and color are printed, motor operates step number, the revolution ratio of driving wheel and driven wheel.
5. method according to claim 1, which is characterized in that the memory module is flash memory type storage chip.
6. method according to claim 1, which is characterized in that the parsing module is used to parse the type of shaped article, into
Row merger processing will have one series of feature merger of triggering relationship between same section and component.
7. method according to claim 1, which is characterized in that the aggregation module obtains type and the feature system of all over products
Column calculate the similarity between product, and are sorted out according to the similarity of the product.
8. method according to claim 1, which is characterized in that the application module, the classification offer for product match
Network service.
9. method according to claim 1, which is characterized in that high energy heat source described in step 1) be laser beam, electron beam, etc.
Ion or ion beam, the material are nonmetallic materials.
10. method according to claim 2, which is characterized in that the dispatching algorithm based on genetic algorithm includes following step
It is rapid:
(1) for the print request of client after being uploaded to server, server timer-triggered scheduler periodically counts newest print request,
On the one hand it concentrates the scheduling of task more, be convenient for changing and adjust, so that scheduling is more efficient and accurate, on the other hand
Calculation amount can be reduced, system load is reduced；
(2) data structure for influencing printing device Scheduling factors is established, data structure includes that client requests class, printer class and beats
Print task class；It includes the location information of print request that the client, which requests class parameter,；The printer class parameter includes that printing is asked
Location information, the printer asked complete the cost of printing, printer completes the time of printing；The print out task class parameter includes
Print out task time-consuming, the overall cost for completing printing, printer side are completed at a distance from client；
(3) it is modeled based on genetic algorithm, i.e., when running up to n client's request within a certain period of time, m printings to be scheduled is set
Standby to carry out unified scheduling, which can be attributed to the optimal layout scheme that n tasks are completed in m platform machine.
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| CN201710438777.XA CN109032538A (en) | 2017-06-12 | 2017-06-12 | Application method of the big data in 3D printing technique |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113878864A (en) * | 2021-08-25 | 2022-01-04 | 青岛理工大学 | Color coding method and 3D printing device |
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| US20120105903A1 (en) * | 2010-08-18 | 2012-05-03 | Pettis Nathaniel B | Networked three-dimensional printing |
| CN104780214A (en) * | 2015-04-20 | 2015-07-15 | 河海大学常州校区 | Cloud manufacturing system and method based on cloud computing and three-dimensional printing |
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| CN105577824A (en) * | 2016-01-28 | 2016-05-11 | 北京航空航天大学 | Cloud manufacturing oriented 3D printing machining task processing method and device |
| CN105946244A (en) * | 2016-06-03 | 2016-09-21 | 湖南华曙高科技有限责任公司 | Method and system for improving three-dimensional object manufacturing precision and three-dimensional object manufacturing equipment |
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2017
- 2017-06-12 CN CN201710438777.XA patent/CN109032538A/en active Pending
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120105903A1 (en) * | 2010-08-18 | 2012-05-03 | Pettis Nathaniel B | Networked three-dimensional printing |
| CN104780214A (en) * | 2015-04-20 | 2015-07-15 | 河海大学常州校区 | Cloud manufacturing system and method based on cloud computing and three-dimensional printing |
| CN105447186A (en) * | 2015-12-16 | 2016-03-30 | 汉鼎信息科技股份有限公司 | Big data platform based user behavior analysis system |
| CN105577824A (en) * | 2016-01-28 | 2016-05-11 | 北京航空航天大学 | Cloud manufacturing oriented 3D printing machining task processing method and device |
| CN105946244A (en) * | 2016-06-03 | 2016-09-21 | 湖南华曙高科技有限责任公司 | Method and system for improving three-dimensional object manufacturing precision and three-dimensional object manufacturing equipment |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113878864A (en) * | 2021-08-25 | 2022-01-04 | 青岛理工大学 | Color coding method and 3D printing device |
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Application publication date: 20181218 |