CN115415542A - Method for predicting performance of duplex stainless steel 3D printing piece based on response surface method - Google Patents
Method for predicting performance of duplex stainless steel 3D printing piece based on response surface method Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 81
- 229910001039 duplex stainless steel Inorganic materials 0.000 title claims abstract description 41
- 230000004044 response Effects 0.000 title claims abstract description 20
- 238000010146 3D printing Methods 0.000 title claims abstract description 17
- 230000008569 process Effects 0.000 claims abstract description 34
- 239000000463 material Substances 0.000 claims description 13
- 238000013507 mapping Methods 0.000 claims description 6
- 239000002245 particle Substances 0.000 claims description 3
- 238000009864 tensile test Methods 0.000 claims description 3
- 238000002844 melting Methods 0.000 abstract description 8
- 230000008018 melting Effects 0.000 abstract description 8
- 230000001808 coupling effect Effects 0.000 abstract description 5
- 238000005516 engineering process Methods 0.000 abstract description 5
- 238000010309 melting process Methods 0.000 abstract description 2
- 238000007639 printing Methods 0.000 abstract description 2
- 238000012360 testing method Methods 0.000 description 5
- 239000000843 powder Substances 0.000 description 4
- 230000007547 defect Effects 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 238000002360 preparation method Methods 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 239000010410 layer Substances 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000000691 measurement method Methods 0.000 description 2
- 239000002184 metal Substances 0.000 description 2
- 229910052751 metal Inorganic materials 0.000 description 2
- 238000004904 shortening Methods 0.000 description 2
- 229910000963 austenitic stainless steel Inorganic materials 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 229910052799 carbon Inorganic materials 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000002542 deteriorative effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000011229 interlayer Substances 0.000 description 1
- 229910052757 nitrogen Inorganic materials 0.000 description 1
- 238000011056 performance test Methods 0.000 description 1
- 229910052698 phosphorus Inorganic materials 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 230000007480 spreading Effects 0.000 description 1
- 238000003892 spreading Methods 0.000 description 1
- 229910001220 stainless steel Inorganic materials 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 238000005482 strain hardening Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B22—CASTING; POWDER METALLURGY
- B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
- B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
- B22F10/20—Direct sintering or melting
- B22F10/28—Powder bed fusion, e.g. selective laser melting [SLM] or electron beam melting [EBM]
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B22—CASTING; POWDER METALLURGY
- B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
- B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
- B22F10/30—Process control
- B22F10/36—Process control of energy beam parameters
- B22F10/366—Scanning parameters, e.g. hatch distance or scanning strategy
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B22—CASTING; POWDER METALLURGY
- B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
- B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
- B22F10/80—Data acquisition or data processing
- B22F10/85—Data acquisition or data processing for controlling or regulating additive manufacturing processes
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- 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
- B33Y10/00—Processes of additive manufacturing
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- 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
- B33Y50/02—Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P10/00—Technologies related to metal processing
- Y02P10/25—Process efficiency
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Abstract
The invention provides a method for predicting the performance of a duplex stainless steel 3D printing piece based on a response surface method, which comprises the following steps of firstly preparing duplex stainless steel samples by adopting selective laser melting process parameters of different levels; further measuring related performance parameters of the duplex stainless steel sample; and finally, establishing a selective laser melting technology to prepare a duplex stainless steel performance prediction model according to the process parameters and the performance parameters. The method provided by the invention comprehensively considers the coupling effect among different process parameters, reasonably constructs the performance prediction model, can effectively predict the density and the mechanical property of the sample through the process parameters, further determines the reasonable process parameter range, can effectively simplify the exploration process of SLM printing process parameters, and provides theoretical reference for preparing high-performance duplex stainless steel.
Description
Technical Field
The invention belongs to the technical field of metal 3D printing, and particularly relates to a method for predicting the performance of a duplex stainless steel 3D printing piece based on a response surface method.
Background
Duplex Stainless Steel (DSS) has both the advantages of ferritic Stainless Steel and austenitic Stainless Steel, has good comprehensive mechanical properties and excellent corrosion resistance, and is widely applied to petrochemical industry, equipment manufacturing industry, aerospace, ocean engineering, automobile industry and other industries. However, due to different strain hardening behaviors of two phases in the duplex stainless steel, the two phases are deformed unevenly and have poor harmony, so that the duplex stainless steel has high hot working difficulty, and the defects of edge cracks, surface cracks and the like are easy to appear during processing, thereby seriously restricting the expansion of the duplex stainless steel in the aspect of preparing complex parts. A Selective Laser Melting (SLM) technology is an important branch in a 3D printing technology, can well solve the forming problem of complex parts, and is used for building a three-dimensional model based on a computer system, and forming solid parts by accumulating layer by layer from bottom to top by adopting Laser Melting metal powder. The SLM technology has the advantages of direct forming, no need of a mold, capability of manufacturing high-precision parts and the like, endows the material with excellent mechanical properties, and is widely applied to aerospace, biomedical treatment, power energy and related fields.
The performance of the SLM forming part is greatly influenced by the process parameters such as laser power, scanning speed and scanning distance. The unreasonable selection of process parameters can cause the defects of insufficient powder melting, discontinuous melting channel, melt splashing and the like in the material, thereby reducing the density of the sample and simultaneously deteriorating the mechanical property of the material. Therefore, reasonable process parameters are selected to effectively improve the compactness and the mechanical property of the sample and prepare the high-quality duplex stainless steel. However, no theory or method is found at present, which can accurately predict the compactness and the mechanical property of the sample through the process parameters.
Therefore, a method capable of effectively predicting the density and the mechanical property of the sample through the process parameters is needed, so as to predict the density and the mechanical property of the sample under different process parameters, further determine a reasonable process parameter range, and provide theoretical reference for preparing high-performance duplex stainless steel.
Disclosure of Invention
Aiming at the blank and the defects in the prior art, the invention aims to provide a method for predicting the performance of a duplex stainless steel 3D printing piece based on a response surface method. The density and the mechanical property of the duplex stainless steel sample prepared by 3D printing are predicted through the process parameters, so that a reasonable process parameter range is determined, and the selection of part process parameters is guided.
In order to achieve the purpose, the invention provides an efficient and accurate prediction method for density and performance of duplex stainless steel prepared by 3D printing by adopting a statistical method, and a nonlinear mapping relation between process parameters (laser power, scanning speed and scanning distance) and material performance (density and tensile strength) is established by adopting a response surface method to realize prediction of the performance of duplex stainless steel prepared by 3D printing.
Firstly, preparing a duplex stainless steel sample by adopting selective laser melting process parameters of different levels; further measuring related performance parameters of the duplex stainless steel sample; and finally, establishing a selective laser melting technology to prepare a duplex stainless steel performance prediction model according to the process parameters and the performance parameters. The method provided by the invention comprehensively considers the coupling effect among different process parameters, reasonably constructs a performance prediction model, can effectively predict the density and the mechanical property of the sample through the process parameters, further determines a reasonable process parameter range, can effectively simplify the exploration process of SLM printing process parameters, and provides theoretical reference for preparing high-performance duplex stainless steel.
The invention specifically adopts the following technical scheme:
a method for predicting the performance of a duplex stainless steel 3D printing piece based on a response surface method is characterized by comprising the following steps:
step 1: selecting different laser power, scanning speed and scanning interval, and preparing a duplex stainless steel sample by using the SLM;
step 2: measuring the density and tensile strength of the sample;
and 3, step 3: and establishing a nonlinear mapping relation among the laser power, the scanning speed and the scanning distance and between the density and the tensile strength of the material by adopting a response surface method, establishing a performance prediction model, and realizing the prediction of the density and the tensile strength of the material by using the process parameters.
Further, in step 1, the duplex stainless steel is used as a material, and the SLM forms the grain sample and the dumbbell sample by changing the process parameters including the laser power, the scanning speed and the scanning distance.
Further, in the step 2, the density of the sample is measured by adopting an Archimedes drainage method, the density is calculated, the tensile strength of the sample is measured by adopting a unidirectional tensile test, and a sample required by a response surface method is obtained.
Further, in step 3, a response surface method is adopted to establish a nonlinear mapping relation among laser power, scanning speed and scanning distance, material density and tensile strength, so that the prediction of the performance of the 3D printing preparation of the duplex stainless steel is realized.
Further, the prediction model established in step 3 is as follows:
a density prediction model: z =19.57544+0.314458 × P +0.004998 × V +1094.8642 × S +0.000012 × P × V-1.12346 × P × S +0.130864 × V × S-0.00047 × P 2 -0.000015×V 2 -6375.85734×S 2 。
Prediction model of tensile strength: k = -2059.75579+14.04277 xP-1.5585 xV +49318.27628 xS +0.004184 xP xV-71.77963 xP x S +15.84432 xV x S-0.022328 xP 2 -0.000617×V 2 -2.85E+05×S 2 。
Wherein Z is density and K tensile strength, P is laser power, V is scanning speed, and S is scanning interval.
Compared with the prior art, the invention and the optimal selection scheme thereof consider the coupling effect among different process parameters and can reliably and accurately predict the performance of the SLM for preparing the duplex stainless steel, thereby further evaluating the rationality of the selective laser melting preparation process parameters and effectively shortening the processing period of products.
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The invention is described in further detail below with reference to the following figures and detailed description:
FIG. 1 is a flow chart of a method for predicting the performance of a duplex stainless steel 3D print based on a response surface method according to an embodiment of the invention;
FIG. 2 is a diagram showing the relationship between the predicted value and the actual value of the density model according to the embodiment of the present invention;
FIG. 3 is a graph of predicted values versus actual values for the tensile strength model of an embodiment of the present invention.
Detailed Description
In order to make the features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail as follows:
in order to further understand the proposed method of the present invention, those skilled in the art will now be described with reference to specific examples. The present invention is further described in the preferred embodiments, which should not be construed as limited to the embodiments set forth herein, nor should it be construed as limited to the scope of the invention which is to be protected by the claims.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure herein. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
As shown in fig. 1, the overall flowchart of the method for predicting the performance of duplex stainless steel manufactured by 3D printing provided in this embodiment includes the following steps:
step 1: and selecting different laser power, scanning speed and scanning distance, and preparing the duplex stainless steel sample by the SLM. The method specifically comprises the following steps: the particle size of the formed powder is 10 to 53 mu m, and the components are less than or equal to 0.02 percent of C, less than or equal to 0.45 percent of Si, less than or equal to 1.0 percent of Mn, less than or equal to 0.02 percent of S, less than or equal to 0.03 percent of P, and Ni:4.5 to 6.5%, cr:21 to 23%, mo:2.5 to 3.5%, N:0.1 to 0.3 percent, and the balance being Fe. The forming process adopts snake-shaped scanning, the interlayer rotation angle is 90 degrees, the laser power is 220-280W, the scanning speed is 500-800mm/s, the scanning distance is 63-77 mu m, the powder spreading thickness is fixed to be 30 mu m, and a printed particle sample and a dumbbell sample are used for measuring the density and the tensile strength.
Step 2: and measuring the density and the mechanical property of the sample. Specifically, the density and tensile strength of the sample formed in step 1 were measured and calculated. First, the density of the sample was measured by Archimedes drainage method and the theoretical density was 7.8g/cm 3 And (6) calculating the density. Then, a tensile test is carried out by using a universal testing machine to obtain the tensile strength, and the loading speed is 2mm/min. It should be noted that the above measurement method is only an example, and other measurement methods to obtain the above related parameters are equivalent to the equivalent techniques and also belong to the protection scope of the present invention. The results of the test piece property test are shown in Table 1.
TABLE 1 test sample Performance test results
And step 3: and establishing a nonlinear mapping relation among the laser power, the scanning speed, the scanning distance, the material density and the tensile strength by adopting a quadratic polynomial regression model in a response surface method. The density and tensile strength prediction model is established as follows:
a density prediction model: z =19.57544 ca 0.314458 XP +0.004998 XV +1094.8642 XS +0.000012 XP XV-1.12346 XPS+0.130864×V×S-0.00047×P 2 -0.000015×V 2 -6375.85734×S 2 。
Prediction model of tensile strength: k = -2059.75579+14.04277 xP-1.5585 xV +49318.27628 xS +0.004184 xP xV-71.77963 xP x S +15.84432 xV x S-0.022328 xP 2 -0.000617×V 2 -2.85E+05×S 2 。
Wherein Z is density and K tensile strength, P is laser power, V is scanning speed, and S is scanning interval. The construction of the prediction model comprehensively considers the coupling effect between different process parameters. The relationship between the predicted value and the actual value of the density and tensile strength prediction models is shown in fig. 2 and 3 respectively. As can be seen from the figure, the actual value is very close to the predicted value, which shows that the established model has higher accuracy.
By using the prediction model established by the method, two groups of process parameters are randomly selected for prediction and actual tests are carried out, and the results are shown in table 2. As can be seen from Table 2, the errors of all the indexes are within 5%, which indicates that the density and tensile strength of the SLM-formed duplex stainless steel can be well predicted by the prediction model established by the method of the present embodiment under different process parameters.
TABLE 2 comparison of model predicted values to actual values
The invention comprehensively considers the coupling effect among different process parameters and can reliably and accurately predict the performance of the SLM for preparing the duplex stainless steel, thereby further evaluating the rationality of the process parameters of the selective laser melting preparation and effectively shortening the processing period of products. The present invention is not limited to the above preferred embodiments, and any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
The above description of the embodiments is only intended to facilitate the understanding of the method of the invention and its core idea. While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention. However, any simple modification, equivalent change and modification of the above embodiments according to the technical essence of the present invention are within the protection scope of the technical solution of the present invention.
Claims (5)
1. A method for predicting the performance of a duplex stainless steel 3D printing member based on a response surface method is characterized by comprising the following steps:
step 1: selecting different laser power, scanning speed and scanning interval, and preparing a duplex stainless steel sample by using the SLM;
step 2: measuring the density and tensile strength of the sample;
and step 3: and establishing a nonlinear mapping relation among the laser power, the scanning speed and the scanning distance and between the density and the tensile strength of the material by adopting a response surface method, establishing a performance prediction model, and realizing the prediction of the density and the tensile strength of the material by using the process parameters.
2. The method for predicting the performance of a duplex stainless steel 3D printer based on the response surface method as claimed in claim 1, wherein in step 1, the duplex stainless steel is used as a material, and the particle samples and the dumbbell samples are SLM-formed by changing the process parameters including laser power, scanning speed and scanning distance.
3. The method for predicting the performance of the duplex stainless steel 3D printing member based on the response surface method as claimed in claim 1, wherein in the step 2, the density of the sample is measured by adopting an Archimedes drainage method, the compactness is calculated, the tensile strength of the sample is measured by adopting a one-way tensile test, and the sample required by the response surface method is obtained.
4. The method for predicting the performance of the duplex stainless steel 3D printing member based on the response surface method as claimed in claim 1, wherein in step 3, the response surface method is adopted to establish the nonlinear mapping relationship among the laser power, the scanning speed and the scanning distance, and the density and the tensile strength of the material, so as to predict the performance of the duplex stainless steel prepared by 3D printing.
5. The method for predicting the performance of a duplex stainless steel 3D print based on the response surface method according to claim 1, wherein the prediction model established in step 3 is as follows:
a density prediction model: z =19.57544+0.314458 × P +0.004998 × V +1094.8642 × S +0.000012 × P × V-1.12346 × P × S +0.130864 × V × S-0.00047 × P 2 -0.000015×V 2 -6375.85734×S 2
Prediction model of tensile strength: k = -2059.75579+14.04277 XP-1.5585 XV +49318.27628 XS +0.004184 XP XV-71.77963 XP XS +15.84432 XV-0.022328 XP 2 -0.000617×V 2 -2.85E+05×S 2
Wherein Z is density and K tensile strength, P is laser power, V is scanning speed, and S is scanning interval.
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