CN108763801A - A kind of laser gain material remanufactures cladding layer geometric properties and dilution rate modeling method - Google Patents

A kind of laser gain material remanufactures cladding layer geometric properties and dilution rate modeling method Download PDF

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CN108763801A
CN108763801A CN201810562315.3A CN201810562315A CN108763801A CN 108763801 A CN108763801 A CN 108763801A CN 201810562315 A CN201810562315 A CN 201810562315A CN 108763801 A CN108763801 A CN 108763801A
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cladding layer
dilution rate
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geometric properties
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岳海涛
郭辰光
李强
赵丽娟
王闯
张建卓
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Liaoning Technical University
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Abstract

A kind of laser gain material of present invention offer remanufactures cladding layer geometric properties and dilution rate modeling method, is related to laser gain material re-manufacturing technology field.This method carries out single cladding road experiment of single factor and obtains technological parameter preferred scope and model verify data first;Single cladding road orthogonal experiment is carried out again obtains more excellent parameter combination and model modeling data;And cladding layer cross-section samples are obtained by cutting sample, cladding layer cross section geometry is measured, dilution rate is calculated;Cladding layer geometric properties and dilution rate interaction linear regression relation equation are finally established, and relational expression coefficient are solved and verified by BreedPSO algorithms fitting and the precision of prediction of model.Laser gain material provided by the invention remanufactures cladding layer geometric properties and dilution rate modeling method, it accurately solves laser gain material and remanufactures the technical problem that fitting precision is not high between single cladding road geometric properties forming dimension and technological parameter, modeling method is simple, accuracy is high, can save production cost.

Description

A kind of laser gain material remanufactures cladding layer geometric properties and dilution rate modeling method
Technical field
The present invention relates to laser gain material re-manufacturing technology fields more particularly to a kind of laser gain material to remanufacture cladding layer geometry Feature and dilution rate modeling method.
Background technology
Laser gain material re-manufacturing technology is a kind of advanced manufacture that material successively or point by point is accumulated product using laser Technology.Then the technology utilizes laser melting coating, laser using the waste and old parts for having lost use value as remanufacturing old parts Advanced manufacturing technology based on rapid prototyping technology carries out injury repair, performance boost to it, so that laser gain material is made again Product after making meets the requirement of new product in quality and performance.Laser gain material re-manufacturing technology great advantage exists A variety of first systems such as Computer-aided Design Technology, Computerized Numerical Control processing technology, material technology and laser processing technology have been merged in it Technology is made, the cladding layer better than basis material performance is produced with comprehensive advanced technology, since the energy density of laser is high Degree is concentrated, and basis material is small to coating material dilution rate, so that the structure property of coating material can be protected, processing Precision is high, and controllability is strong, and the coating material that the high-energy of laser can be processed is in extensive range.
Single track cladding remanufactures the basic component units of shaped structure as laser gain material, and multi-track overlapping and lamination forming are all It is to realize that its shaped structure is largely fixed the entirety of overlap joint and lamination with the roads single cladding Dao Zhu overlap joint, tired pile Shape characteristic.Exactly this local pattern of single track cladding is uneven, so as to cause the whole structure mistake for increasing material and remanufacturing forming Difference, if mustn't go to control, it might even be possible to lead to the failure of once-forming processing.The geometric feature sizes in single cladding road and internal group It knits structure and represents the integrity attribute that laser gain material remanufactures shaped structure to a certain extent, therefore, to the geometry in single cladding road The research of shape characteristic and dilution rate is necessary.
Invention content
In view of the drawbacks of the prior art, a kind of laser gain material of present invention offer remanufactures cladding layer geometric properties and dilution rate Modeling method, realization model the geometrical morphology feature and dilution rate in single cladding road.
A kind of laser gain material remanufactures cladding layer geometric properties and dilution rate modeling method, includes the following steps:
Step 1 remanufactures single cladding road experiment of single factor by laser gain material, obtains and cladding layer geometric properties and dilution It the preferred scope of the relevant technological parameter of rate and tests what single cladding road geometrical morphology feature and dilution rate model were verified Demonstrate,prove data;
Described and cladding layer geometric properties and the relevant technological parameter of dilution rate include laser power P, scan velocity VSWith Powder feeding rate VF
Step 2 is obtained and cladding layer geometric properties and the relevant technological parameter of dilution rate by single cladding road orthogonal experiment More excellent parameter combination and model modeling data, specific method is:
The test specimen of cutting single cladding road orthogonal experiment obtains cladding layer cross-section samples, surpasses depth of field three-dimensional microscope by optics Measure cladding layer geometric properties, including cladding height H, cladding layer cross-sectional area SRWith matrix melts area SJ;And pass through cladding layer Geometric properties calculate dilution rate λ, shown in following formula:
[SJ/(SR+SJ)] × 100%
Cladding height H, cross-sectional area S by the cladding layer obtained to measurementRWith matrix melts area SJAnd it calculates The dilution rate λ arrived carries out the more excellent parameter group of range analysis determination and cladding layer geometric properties and the relevant technological parameter of dilution rate It closes;And by the cladding height H of cladding layer, cross-sectional area SRWith matrix melts area SJAnd dilution rate λ is as single cladding road cladding The initial data of layer geometric properties and dilution rate model;
Step 3, establish single cladding road cladding layer geometric properties and dilution rate interaction linear regression relation formula, and pass through Population BreedPSO algorithms based on hybridization theory solve the coefficient in relational expression, complete to single cladding road cladding layer The modeling of geometric properties and dilution rate;
The specific method of the interaction linear regression relation formula for establishing cladding layer geometric properties and dilution rate is:
Technological parameter and cladding layer geometric properties and dilution are established based on the quadratic regression model with interaction coefficient The regression relation of rate, shown in following formula:
Wherein, H (P, VS, VF) it is cladding layer height, SR(P, VS, VF) it is cladding layer cross-sectional area, SJ(P, VS, VF) it is base Body melting area, λ (P, VS, VF) it is dilution rate, α0、β0、χ0And δ0It is the constant term coefficient of regression equation, αi、βi、χiAnd δi The Monomial coefficient of regression equation, αii、βii、χiiAnd δiiIt is the two-term coefficient of regression equation, αij、βij、χijAnd δijIt is The interaction coefficient of regression equation, i=1,2,3, j=1,2,3, and i ≠ j, ε are error term;
The fitting precision and precision of prediction of step 4, verification single cladding road cladding layer geometric properties and dilution rate model, specifically Method is:
Single cladding road cladding layer geometric properties and dilution rate model are calculated using coefficient of multiple determination R shown in following formula Fitting precision:
Wherein, n is test specimen sample number used in single cladding road orthogonal experiment, yiFor the measured value of single cladding road orthogonal experiment, For the match value of single cladding road cladding layer geometric properties and dilution rate model, i '=1,2 ..., n;
Bring cladding layer geometric properties and the relevant technological parameter of dilution rate that single cladding road experiment of single factor obtains into list Cladding road cladding layer geometric properties and dilution rate model measure the cladding layer geometric feature sizes and dilution rate that acquire with practical Obtained data are compared, and the single cladding road cladding layer geometric properties of predictive coefficient verification shown in following formula and dilution are passed through The precision of prediction of rate model:
Wherein, η is predictive coefficient.
As shown from the above technical solution, the beneficial effects of the present invention are:A kind of laser gain material provided by the invention is made again Cladding layer geometric properties and dilution rate modeling method are made, existing method is overcome and determines cladding layer geometric properties and dilution rate and work The limitation of regression relation between skill parameter accurately solves laser gain material and remanufactures single cladding road geometric properties forming dimension The not high technical problem of fitting precision between technological parameter, modeling method is simple, accuracy is high, can save production cost, Theories integration can be provided for overlap joint and lamination cladding simultaneously.
Description of the drawings
Fig. 1 is that a kind of laser gain material provided in an embodiment of the present invention remanufactures cladding layer geometric properties and dilution rate modeling side The flow chart of method;
Fig. 2 is test specimen schematic diagram used in single cladding road provided in an embodiment of the present invention experiment of single factor;
Fig. 3 is the cross section geometric feature schematic diagram in single cladding road provided in an embodiment of the present invention;
Fig. 4 is DD-02 test specimens actual measured results figure provided in an embodiment of the present invention;
Fig. 5 is the orthogonal test meter of single cladding road cladding layer geometric properties and dilution rate provided in an embodiment of the present invention The comparing result figure of calculation value and models fitting value;
Fig. 6 is the orthogonal test meter of single cladding road cladding layer geometric properties and dilution rate provided in an embodiment of the present invention The comparing result figure of calculation value and model predication value.
In figure, 1, cladding layer;2, substrate material;3, matrix melts area SJ;4, heat affected area;5, cladding height H;6, it melts Coating cross-sectional area SR;7, the measurement section of DD-02 test specimens;
Specific implementation mode
With reference to the accompanying drawings and examples, the specific implementation mode of the present invention is described in further detail.Implement below Example is not limited to the scope of the present invention for illustrating the present invention.
A kind of laser gain material remanufactures cladding layer geometric properties and dilution rate modeling method, as shown in Figure 1, such as including step Under:
Step 1 remanufactures single cladding road experiment of single factor by laser gain material, obtains and cladding layer geometric properties and dilution It the preferred scope of the relevant technological parameter of rate and tests what single cladding road geometrical morphology feature and dilution rate model were verified Demonstrate,prove data;
Include laser power P, scan velocity V with cladding layer geometric properties and the relevant technological parameter of dilution rateSAnd powder feeding Rate VF
The present embodiment selects 34GrNiMO6 as basis material, using the ferrochrome powder of preparation as cladding material Material, according to the initial range of process equipment characteristic selection and cladding layer geometric properties and the relevant technological parameter of dilution rate, wherein The initial range of laser power P is 900~1400W, scan velocity VSInitial range be 700~1200mm/min, powder feeding speed Rate VFInitial range be 3.2~4.1rad/min, specific experiment of single factor protocol is as shown in table 1, according to as shown in Figure 2 Experimental result determine optimizing technology parameters ranging from:P=1100~1400W, VS=700~1000mm/min, VF=3.2~ 4.1rad/min。
1 experiment of single factor protocol of table
Step 2 is obtained and cladding layer geometric properties and the relevant technological parameter of dilution rate by single cladding road orthogonal experiment More excellent parameter combination and model modeling data, specific method is:
The test specimen of cutting single cladding road orthogonal experiment obtains cladding layer cross-section samples, surpasses depth of field three-dimensional microscope by optics Measure cladding layer geometric properties, including cladding height H, cladding layer cross-sectional area SRWith matrix melts area SJ;And pass through cladding layer Geometric properties calculate dilution rate λ, shown in following formula:
[SJ/(SR+SJ)] × 100%
Cladding height H, cross-sectional area S by the cladding layer obtained to measurementRWith matrix melts area SJAnd it calculates The dilution rate λ arrived carries out the more excellent parameter group of range analysis determination and cladding layer geometric properties and the relevant technological parameter of dilution rate It closes;And by the cladding height H of cladding layer, cross-sectional area SRWith matrix melts area SJAnd dilution rate λ is as single cladding road cladding The initial data of layer geometric properties and dilution rate model;
In the present embodiment, single cladding road orthogonal experiment protocol is as shown in table 2, by measuring obtained cladding layer Cladding height H, cross-sectional area SRWith matrix melts area SJAnd the dilution rate λ being calculated carries out range analysis and determines and melt The more excellent parameter combination of coating geometric properties and the relevant technological parameter of dilution rate is laser power P=1300W, scan velocity VS =700mm/min, powder feeding rate VF=3.5rad/min;And by the cladding height H of cladding layer, cross-sectional area SRAnd matrix melts Initial data of the area SJ and dilution rate λ as single cladding road cladding layer geometric properties and dilution rate model.
The single cladding of table 2 road orthogonal experiment protocol
Step 3, establish single cladding road cladding layer geometric properties and dilution rate interaction linear regression relation formula, and pass through Population BreedPSO algorithms based on hybridization theory solve the coefficient in relational expression, complete to single cladding road cladding layer The modeling of geometric properties and dilution rate;
The specific method for establishing the interaction linear regression relation formula of cladding layer geometric properties and dilution rate is:
Technological parameter and cladding layer geometric properties and dilution are established based on the quadratic regression model with interaction coefficient The regression relation of rate, shown in following formula:
Wherein, H (P, VS, VF)、SR(P, VS, VF)、SJ(P, VS, VF) and λ (P, VS, VF) it is respectively cladding layer height, cladding Layer cross-sectional area, matrix melts area and dilution rate, α0、β0、χ0And δ0It is the constant term coefficient of regression equation, αi、βi、χiWith δiThe Monomial coefficient of regression equation, αii、βii、χiiAnd δiiIt is the two-term coefficient of regression equation, αij、βij、χijWith δ ij? For the interaction coefficient of regression equation, i=1,2,3, j=1,2,3, and i ≠ j, ε are error term.
In the present embodiment, cladding road cross section geometric feature is as shown in figure 3, DD-02 test specimens actual measured results such as Fig. 4 institutes Show, experiment of single factor survey calculation data are as shown in table 3, and orthogonal experiment survey calculation data are as shown in table 4.
3 experiment of single factor survey calculation data of table
4 orthogonal experiment survey calculation data of table
In the present embodiment, cladding height H, cladding layer cross-sectional area SR, matrix melts area SJWith the interaction line of dilution rate λ Property regression model is as follows:
The fitting precision and precision of prediction of step 4, verification single cladding road cladding layer geometric properties and dilution rate model, specifically Method is:
Single cladding road cladding layer geometric properties and dilution rate model are calculated using coefficient of multiple determination R shown in following formula Fitting precision:
Wherein, n is test specimen sample number used in single cladding road orthogonal experiment, yiFor the measured value of single cladding road orthogonal experiment, For the match value of single cladding road cladding layer geometric properties and dilution rate model, i '=1,2 ..., n;
Bring cladding layer geometric properties and the relevant technological parameter of dilution rate that single cladding road experiment of single factor obtains into list Cladding road cladding layer geometric properties and dilution rate model measure the cladding layer geometric feature sizes and dilution rate that acquire with practical Obtained data are compared, and the single cladding road cladding layer geometric properties of predictive coefficient verification shown in following formula and dilution are passed through The precision of prediction of rate model:
Wherein, η is predictive coefficient.
In the present embodiment, the model digital simulation value based on orthogonal test combination of process parameters is as shown in table 5, cladding height H, cladding layer cross-sectional area SR, matrix melts area SJModels fitting comparison with dilution rate λ is determined as shown in figure 5, being computed repetition measurement Coefficients R2Respectively 0.9995,0.9992,0.9990,0.9998.
The match value that model of the table 5 based on orthogonal test combination of process parameters calculates
In the present embodiment, brings single cladding road experiment of single factor combination of process parameters into mathematical model, will ask as shown in table 6 The geometric feature sizes and dilution rate match value obtained, and the comparison practical survey calculation data of experiment of single factor, pass through and predict system The precision of prediction of number formula verification mathematical model.
In the present embodiment, established cladding height H, cladding layer cross-sectional area S are shown by verification resultR, matrix it is molten Change area SJ95.08%, 92.02%, 88.32% is respectively reached with the precision of prediction of the interaction linear regression model (LRM) of dilution rate λ, 96.94%, model proving and comparisom is as shown in Figure 6.
The geometric feature sizes and dilution rate match value in the single cladding of table 6 road
Finally it should be noted that:The above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations;Although Present invention has been described in detail with reference to the aforementioned embodiments, it will be understood by those of ordinary skill in the art that:It still may be used To modify to the technical solution recorded in previous embodiment, either which part or all technical features are equal It replaces;And these modifications or replacements, model defined by the claims in the present invention that it does not separate the essence of the corresponding technical solution It encloses.

Claims (5)

1. a kind of laser gain material remanufactures cladding layer geometric properties and dilution rate modeling method, it is characterised in that:Including following step Suddenly:
Step 1 remanufactures single cladding road experiment of single factor by laser gain material, obtains and cladding layer geometric properties and dilution rate phase The preferred scope of the technological parameter of pass and the verification number that single cladding road geometrical morphology feature and dilution rate model are verified According to;
Step 2, by single cladding road orthogonal experiment obtain with cladding layer geometric properties and the relevant technological parameter of dilution rate compared with Excellent parameter combination and model modeling data;
Step 3, establish single cladding road cladding layer geometric properties and dilution rate interaction linear regression relation formula, and by being based on The population BreedPSO algorithms of hybridization theory solve the coefficient in relational expression, complete to single cladding road cladding layer geometry The modeling of feature and dilution rate;
The fitting precision and precision of prediction of step 4, verification single cladding road cladding layer geometric properties and dilution rate model.
2. a kind of laser gain material according to claim 1 remanufactures cladding layer geometric properties and dilution rate modeling method, It is characterized in that:Include laser power P, scan speed with cladding layer geometric properties and the relevant technological parameter of dilution rate described in step 1 Spend VSWith powder feeding rate VF
3. a kind of laser gain material according to claim 2 remanufactures cladding layer geometric properties and dilution rate modeling method, It is characterized in that:Step 2 specific method is:
The test specimen of cutting single cladding road orthogonal experiment obtains cladding layer cross-section samples, surpasses depth of field three-dimensional by optics and is measured microscopically Cladding layer geometric properties, including cladding height H, cladding layer cross-sectional area SRWith matrix melts area SJ;And pass through cladding layer geometry Feature calculation dilution rate λ, shown in following formula:
[SJ/(SR+SJ)] × 100%
Cladding height H, cross-sectional area S by the cladding layer obtained to measurementRWith matrix melts area SJAnd be calculated Dilution rate λ carries out the more excellent parameter combination of range analysis determination and cladding layer geometric properties and the relevant technological parameter of dilution rate; And by the cladding height H of cladding layer, cross-sectional area SRWith matrix melts area SJAnd dilution rate λ is as single cladding road cladding layer The initial data of geometric properties and dilution rate model.
4. a kind of laser gain material according to claim 3 remanufactures cladding layer geometric properties and dilution rate modeling method, It is characterized in that:The specific side of the interaction linear regression relation formula of cladding layer geometric properties and dilution rate is established described in the step 3 Method is:
Technological parameter and cladding layer geometric properties and dilution rate are established based on the quadratic regression model with interaction coefficient Regression relation, shown in following formula:
Wherein, H (P, VS, VF) it is cladding layer height, SR(P, VS, VF) it is cladding layer cross-sectional area, SJ(P, VS, VF) melted for matrix Change area, λ (P, VS, VF) it is dilution rate, α0、β0、χ0And δ0It is the constant term coefficient of regression equation, αi、βi、χiAnd δiIt returns The Monomial coefficient of equation, αii、βii、χiiAnd δiiIt is the two-term coefficient of regression equation, αij、βij、χijAnd δijIt is to return The interaction coefficient of equation, i=1,2,3, j=1,2,3, and i ≠ j, ε are error term.
5. a kind of laser gain material according to claim 4 remanufactures cladding layer geometric properties and dilution rate modeling method, It is characterized in that:Step 4 specific method is:
The fitting of single cladding road cladding layer geometric properties and dilution rate model is calculated using coefficient of multiple determination R shown in following formula Precision:
Wherein, n is test specimen sample number used in single cladding road orthogonal experiment, yiFor the measured value of single cladding road orthogonal experiment,For list The match value of cladding road cladding layer geometric properties and dilution rate model, i '=1,2 ..., n;
Bring cladding layer geometric properties and the relevant technological parameter of dilution rate that single cladding road experiment of single factor obtains into single cladding Road cladding layer geometric properties and dilution rate model obtain the cladding layer geometric feature sizes acquired and dilution rate with practical measurement Data compared, pass through the single cladding road cladding layer geometric properties of predictive coefficient verification and dilution rate mould shown in following formula The precision of prediction of type:
Wherein, η is predictive coefficient.
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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109473145A (en) * 2018-11-07 2019-03-15 桂林电子科技大学 A kind of electron beam cladding process parameter optimizing method and system based on Orthogonal Method
CN112857271A (en) * 2021-01-08 2021-05-28 中国科学院力学研究所 Method for judging stability of laser cladding process
CN113059186A (en) * 2021-03-19 2021-07-02 沈阳工业大学 Low-carbon modeling and process parameter optimization method in laser additive manufacturing process
CN114003003A (en) * 2021-08-04 2022-02-01 上海航天设备制造总厂有限公司 Technological parameter optimization and stability control method in laser cladding process
CN114346260A (en) * 2022-01-04 2022-04-15 大连理工大学 Geometric feature prediction method for laser melting deposition layer
CN115945698A (en) * 2023-03-13 2023-04-11 西安石油大学 Metal cladding layer forming quality optimization method based on CMT additive remanufacturing

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106484968A (en) * 2016-09-23 2017-03-08 西安交通大学 A kind of method for quick predicting of the heat exchange Correlations based on response surface
CN106529129A (en) * 2016-10-21 2017-03-22 武汉理工大学 Cladding layer cross section contour curve under broadband laser effect and modeling method
EP3316156A1 (en) * 2016-11-01 2018-05-02 Xometry, Inc. Methods and apparatus for machine learning predictions of manufacture processes
CN108036735A (en) * 2017-11-29 2018-05-15 武汉理工大学 A kind of broadband laser cladding molten bath contour curve and its modeling method
CN108062433A (en) * 2017-11-26 2018-05-22 中国人民解放军陆军装甲兵学院 The gradient curved surface layered approach of point cloud model is remanufactured based on increasing material

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106484968A (en) * 2016-09-23 2017-03-08 西安交通大学 A kind of method for quick predicting of the heat exchange Correlations based on response surface
CN106529129A (en) * 2016-10-21 2017-03-22 武汉理工大学 Cladding layer cross section contour curve under broadband laser effect and modeling method
EP3316156A1 (en) * 2016-11-01 2018-05-02 Xometry, Inc. Methods and apparatus for machine learning predictions of manufacture processes
CN108062433A (en) * 2017-11-26 2018-05-22 中国人民解放军陆军装甲兵学院 The gradient curved surface layered approach of point cloud model is remanufactured based on increasing material
CN108036735A (en) * 2017-11-29 2018-05-15 武汉理工大学 A kind of broadband laser cladding molten bath contour curve and its modeling method

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
CHENGUANG GUO 等: "pindle static and dynamic characteristics analysis of precision CNC turning center", 《YDRAULIC EQUIPMENT AND SUPPORT SYSTEMS FOR MINING, IWHEM2012》 *
许波: "面向绿色再制造的单道激光熔覆几何特征的研究", 《中国优秀硕士学位论文全文数据库(工程科技Ⅰ辑)》 *

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109473145A (en) * 2018-11-07 2019-03-15 桂林电子科技大学 A kind of electron beam cladding process parameter optimizing method and system based on Orthogonal Method
CN112857271A (en) * 2021-01-08 2021-05-28 中国科学院力学研究所 Method for judging stability of laser cladding process
CN112857271B (en) * 2021-01-08 2022-03-11 中国科学院力学研究所 Method for judging stability of laser cladding process
CN113059186A (en) * 2021-03-19 2021-07-02 沈阳工业大学 Low-carbon modeling and process parameter optimization method in laser additive manufacturing process
CN114003003A (en) * 2021-08-04 2022-02-01 上海航天设备制造总厂有限公司 Technological parameter optimization and stability control method in laser cladding process
CN114346260A (en) * 2022-01-04 2022-04-15 大连理工大学 Geometric feature prediction method for laser melting deposition layer
CN115945698A (en) * 2023-03-13 2023-04-11 西安石油大学 Metal cladding layer forming quality optimization method based on CMT additive remanufacturing
CN115945698B (en) * 2023-03-13 2023-05-23 西安石油大学 Metal cladding layer forming quality optimization method based on CMT additive remanufacturing

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