Additive manufacturing method based on porosity multi-objective constraint

Abstract

The invention relates to the technical field of additive manufacturing, in particular to an additive manufacturing method based on porosity multi-objective constraint, which comprises the step of optimizing process parameters of additive manufacturing based on porosity related parameters of an additive manufacturing finished product. According to the method, a limited number of additive manufacturing finished products with different process parameters are prepared through an orthogonal test, the porosity related parameters of all the finished products are calculated, and the specific threshold value a is set to screen all the finished products; and the finished product with the small porosity related parameters is screened out to serve as the defect-free target sample, the defect-free additive manufacturing finished product and the corresponding defect-free additive manufacturing process can be obtained, and the problems that in additive manufacturing in the prior art, process parameters are difficult to determine, the cost is high, and the defect-free process screening accuracy is poor are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of additive manufacturing, and particularly to an additive manufacturing method based on multi-objective constraints of porosity. Background Art

[0002] Additive manufacturing technology is a manufacturing method that accumulates materials based on 3D model data to form a solid structure, among which laser additive manufacturing is widely used. However, due to the characteristics of the forming process of layer-by-layer stacking and rapid cooling in metal laser additive manufacturing, during the metal laser additive manufacturing process, process parameters such as the laser scanning power, scanning speed, and scanning spacing used will affect the geometric shape of the molten pool and the solidification process such as the cooling rate, thereby affecting the metallurgical quality of the component and generating internal defects such as cracks and pores.

[0003] Currently, the traditional strategy for exploring additive manufacturing parameters is usually: based on the observation of the metallographic structure or scanning electron microscope morphology of the specimen, conducting repeated experiments, exhausting the correspondence between parameters and defects, and then passively screening out the parameters corresponding to specimens with excellent mechanical properties. The traditional strategy for exploring additive manufacturing parameters has a large workload, is time-consuming, and costly; and the defect analysis method based on morphology observation has a certain degree of subjectivity, with poor accuracy in screening defect-free samples, low yield of finished products, and the existing additive manufacturing methods are difficult to meet the requirements of preparing crack-free and pore-free finished products. Summary of the Invention

[0004] In view of the above analysis, the present invention aims to provide an additive manufacturing method based on multi-objective constraints of porosity to solve at least one of the problems existing in additive manufacturing in the prior art, such as difficult determination of process parameters, high cost, poor accuracy in screening defect-free processes, many crack and pore defects, and low yield.

[0005] The object of the present invention is mainly achieved through the following technical solutions:

[0006] An additive manufacturing method based on multi-objective constraints of porosity, the additive manufacturing method based on multi-objective constraints of porosity includes: optimizing the process parameters of additive manufacturing based on the porosity-related parameters of the additive manufacturing finished product.

[0007] Preferably, the additive manufacturing method based on multi-objective constraints of porosity includes:

[0008] S1: Preparing additive manufacturing finished products with different process parameters by setting a four-variable orthogonal experiment based on the process parameters of laser scanning power P, scanning speed v, scanning layer thickness t, and scanning spacing h;

[0009] S2: Selecting samples with the porosity-related parameters of the finished product ≤ a specific threshold a from the additive manufacturing finished products as defect-free target samples;

[0010] S3: Batch prepare defect-free additive manufacturing finished products with the process parameters of the target sample as the additive manufacturing process parameters.

[0011] Preferably, the porosity-related parameter in step S2 is the open porosity, and / or the closed porosity, and / or the total porosity.

[0012] Preferably, the porosity-related parameter of the finished product in step S2 ≤ a specific threshold a satisfies:

[0013] Open porosity ≤ 1%, closed porosity ≤ 1%, total porosity ≤ 2%.

[0014] Preferably, step S2 includes:

[0015] S201: Obtain the apparent density ρ1 and the bulk density ρ2 of the additive manufacturing finished product based on the mass of the additive manufacturing finished product in the dry state and the saturated water-containing state based on the boiling method.

[0016] S202: Obtain the total porosity ε1, open porosity ε2, and closed porosity ε3 of the additive manufacturing finished product based on the apparent density ρ1 and the bulk density ρ2.

[0017] Preferably, step S201 includes:

[0018] S2011: Obtain the mass m1 of the dry additive manufacturing finished product, the floating weight m2 of the additive manufacturing finished product, and the saturated wet weight m3 of the additive manufacturing finished product.

[0019] S2012: Obtain the apparent density ρ1 and the bulk density ρ2 of the additive manufacturing finished product based on the mass m1 of the dry additive manufacturing finished product, the floating weight m2 of the additive manufacturing finished product, and the saturated wet weight m3 of the additive manufacturing finished product.

[0020] Preferably, step S2 further includes:

[0021] S203: Plot a two-dimensional coordinate graph of the open porosity, and / or the closed porosity, and / or the total porosity and the energy density δ to assist in screening the defect-free target sample, where δ satisfies:

[0022] δ = P / (v × h × t).

[0023] Preferably, step S203 includes:

[0024] S2031: Construct a two-dimensional plane coordinate system with the open porosity ε2, and / or the closed porosity ε3, and / or the total porosity ε1 as the ordinate and δ as the abscissa;

[0025] S2032: Draw a first auxiliary identification line with the open porosity ε2 = 1% in the coordinate system. The data points in the area below the first auxiliary identification line correspond to the additive manufacturing finished products with ε2 < 1%.

[0026] And / or, a second auxiliary identification line with a closed porosity ε3 = 1% is drawn in the coordinate system, and the data points in the area below the second auxiliary identification line correspond to the additive manufactured products with ε3 < 1%.

[0027] And / or, a third auxiliary identification line with a total porosity ε1 = 2% is drawn in the coordinate system, and the data points in the area below the third auxiliary identification line correspond to the additive manufactured products with ε1 < 2%.

[0028] S2033: Select the additive manufactured products in the three areas screened in S2032 as the defect-free target samples as needed.

[0029] Preferably, step S2033 includes: taking the intersection of the additive manufactured products in the three areas screened in step S2032 as the defect-free target samples.

[0030] A titanium alloy additive manufactured product is prepared by the above additive manufacturing method.

[0031] Compared with the prior art, the present invention can at least achieve one of the following beneficial effects:

[0032] (1) The present invention prepares a limited number of additive manufactured products with different process parameters through orthogonal experiments, calculates the porosity-related parameters of each product and sets a specific threshold a to screen each product, and selects the products with smaller porosity-related parameters as the defect-free target samples to obtain defect-free additive manufactured products and corresponding defect-free additive manufacturing processes. On the one hand, it avoids the repeated experiments and exhaustion based on specimen metallography or scanning electron microscope morphology observation in the prior art, reducing a large amount of calculation and metallography test workload and cost; on the other hand, the present invention does not perform defect analysis based on morphology observation, thus reducing the error caused by subjectivity, improving the accuracy of the selected target process parameters, and improving the yield of the finally batch-prepared additive manufactured products.

[0033] (2) The present invention takes the intersection of the additive manufactured products that satisfy ε2 < 1%, ε3 < 1% and ε1 < 2% as the defect-free target samples, further improving the accuracy of defect-free process screening and reducing the generation of defects.

[0034] In the present invention, the above technical solutions can also be combined with each other to achieve more preferred combination schemes. Other features and advantages of the present invention will be described in the subsequent specification, and some advantages can be made obvious from the specification, or understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the embodiments of the specification and the content specifically pointed out in the drawings. Description of the Drawings

[0035] The accompanying drawings are only for the purpose of showing specific embodiments and are not considered to be a limitation of the present invention. Throughout the drawings, the same reference signs denote the same components.

[0036] Figure 1 is a drawing exemplarily illustrating the corresponding relationship between energy density and open porosity / closed porosity / total porosity;

[0037] Figure 2 is a graph showing the corresponding relationship between energy density and closed porosity in Example 1 of the present invention;

[0038] Figure 3a is the internal metallographic morphology of the specimen when the power, scanning speed, scanning spacing, and layer thickness in Example 1 of the present invention are (250 W, 1100 mm / s, 0.06 mm, 0.045 mm) respectively;

[0039] Figure 3b is the surface metallographic morphology of the specimen when the power, scanning speed, scanning spacing, and layer thickness in Example 1 of the present invention are (250 W, 1100 mm / s, 0.06 mm, 0.045 mm) respectively;

[0040] Figure 4a is a graph showing the corresponding relationship between energy density and open porosity / closed porosity / total porosity in Example 2 of the present invention;

[0041] Figure 4b is Figure 4a a partial enlarged view of area A of;

[0042] Figure 5a is the internal metallographic morphology of the specimen when the power, scanning speed, scanning spacing, and layer thickness in Example 2 of the present invention are (350 W, 900 mm / s, 0.12 mm, 0.03 mm) respectively;

[0043] Figure 5b is the surface metallographic morphology of the specimen when the power, scanning speed, scanning spacing, and layer thickness in Example 2 of the present invention are (350 W, 900 mm / s, 0.12 mm, 0.03 mm) respectively;

[0044] Figure 6a is the internal metallographic morphology of the specimen when the power, scanning speed, scanning spacing, and layer thickness in Example 2 of the present invention are (200 W, 1700 mm / s, 0.04 mm, 0.03 mm) respectively;

[0045] Figure 6b is the surface metallographic morphology of the specimen when the power, scanning speed, scanning spacing, and layer thickness in Example 2 of the present invention are (200 W, 1700 mm / s, 0.04 mm, 0.03 mm) respectively;

[0046] Figure 7aIt is the metallographic morphology inside the specimen when the power, scanning speed, scanning pitch, and layer thickness in Example 2 of the present invention are (350 W, 1100 mm / s, 0.1 mm, 0.03 mm) respectively;

[0047] Figure 7b It is the metallographic morphology on the surface of the specimen when the power, scanning speed, scanning pitch, and layer thickness in Example 2 of the present invention are (350 W, 1100 mm / s, 0.1 mm, 0.03 mm) respectively;

[0048] Figure 8a It is the metallographic morphology inside the specimen when the power, scanning speed, scanning pitch, and layer thickness in Comparative Example 1 of the present invention are (300 W, 1100 mm / s, 0.10 mm, 0.06 mm) respectively;

[0049] Figure 8b It is the metallographic morphology on the surface of the specimen when the power, scanning speed, scanning pitch, and layer thickness in Comparative Example 1 of the present invention are (300 W, 1100 mm / s, 0.10 mm, 0.06 mm) respectively. Detailed implementation manners

[0050] The following will specifically describe the preferred embodiments of the present invention in conjunction with the accompanying drawings. Among them, the accompanying drawings form a part of the present invention and are used together with the embodiments of the present invention to explain the principle of the present invention, rather than to limit the scope of the present invention.

[0051] Technical terms related to additive manufacturing involved in the present invention:

[0052] Additive manufacturing uses a laser to melt raw material powder, and the laser scans the raw material powder layer along a specific trajectory;

[0053] The laser irradiation power is the laser scanning power P, the thickness of the raw material powder layer is the scanning layer thickness t; the distance between the centers of adjacent laser scanning trajectories is the scanning pitch h; the moving speed of the laser light source is the scanning speed v.

[0054] On the one hand, the present invention discloses an additive manufacturing method based on multi-objective constraints of porosity, including:

[0055] Optimizing the process parameters of additive manufacturing based on the porosity-related parameters of the additive manufacturing finished product.

[0056] Specifically, the additive manufacturing method based on multi-objective constraints of porosity includes:

[0057] S1: Preparing additive manufacturing finished products with different process parameters by setting a four-variable orthogonal experiment based on the process parameters of laser scanning power P, scanning speed v, scanning layer thickness t, and scanning pitch h;

[0058] S2: Select samples with the porosity-related parameters of the finished product ≤ a specific threshold a from the additively manufactured finished products as the defect-free target samples;

[0059] S3: Use the process parameters of the target samples as the process parameters for additive manufacturing to batch produce defect-free additively manufactured finished products.

[0060] Compared with the prior art, the present invention prepares a limited number of additively manufactured finished products with different process parameters through orthogonal experiments, calculates the porosity-related parameters of each finished product and sets a specific threshold a to screen each finished product, and selects the finished products with smaller porosity-related parameters as the defect-free target samples to obtain defect-free additively manufactured finished products and corresponding defect-free additive manufacturing processes. On the one hand, it avoids the repeated experiments and exhaustion based on the metallographic examination of specimens or the morphology observation by scanning electron microscope in the prior art, reducing a large amount of calculation and the workload and cost of metallographic experiments; on the other hand, the present invention does not perform defect analysis based on morphology observation, thus reducing the error caused by subjectivity, improving the accuracy of the selected target process parameters, and improving the yield of the finally batch-produced additively manufactured finished products.

[0061] Specifically, in step S2, the porosity-related parameters are the open porosity, and / or the closed porosity, and / or the total porosity.

[0062] Specifically, the porosity-related parameters of the finished product in step S2 ≤ a specific threshold a satisfy:

[0063] Open porosity ≤ 1%, closed porosity ≤ 1%, total porosity ≤ 2%.

[0064] The applicant's research found that the open porosity, closed porosity, and total porosity of the additively manufactured finished products are positively correlated with the void defects of the finished products. The smaller the above parameters, the fewer the defects such as crack pores in the additively manufactured finished products; when the porosity-related parameters satisfy open porosity ≤ 1%, closed porosity ≤ 1%, and total porosity ≤ 2%, the defects such as crack pores are fewer.

[0065] Specifically, step S2 includes:

[0066] S201: Obtain the apparent density ρ1 of the additively manufactured finished product and the bulk density ρ2 of the additively manufactured finished product based on the mass of the additively manufactured finished product in different moisture content states;

[0067] S202: Obtain the total porosity ε1, open porosity ε2, and closed porosity ε3 of the additively manufactured finished product based on the apparent density ρ1 and the bulk density ρ2.

[0068] Specifically, step S201 includes:

[0069] S2011: Obtain the dry additive manufacturing finished product quality m1, the floating weight m2 of the additive manufacturing finished product, and the saturated wet weight m3 of the additive manufacturing finished product;

[0070] S2012: Obtain the apparent density ρ1 and the bulk density ρ2 of the additive manufacturing finished product based on the dry additive manufacturing finished product quality m1, the floating weight m2 of the additive manufacturing finished product, and the saturated wet weight m3 of the additive manufacturing finished product.

[0071] It should be noted that the differences in the dry additive manufacturing finished product quality m1, the floating weight m2 of the additive manufacturing finished product, and the saturated wet weight m3 of the additive manufacturing finished product are due to different moisture contents in the finished product.

[0072] Specifically, in step S2011, the floating weight m2 of the additive manufacturing finished product is obtained by the boiling method, including:

[0073] Place the additive manufacturing finished product specimen in the immersion liquid and boil it to make the specimen fully saturated. Cool it to room temperature and measure the mass of the saturated specimen in the immersion liquid, which is the floating weight m2 of the additive manufacturing finished product.

[0074] Specifically, the method for obtaining the saturated wet weight m3 of the additive manufacturing finished product in step S2011 is as follows:

[0075] Place the additive manufacturing finished product specimen in the immersion liquid and boil it to make the specimen fully saturated. Cool it to room temperature and wipe off the residual liquid on the surface of the specimen with a cotton cloth saturated with the same immersion liquid, and weigh it to obtain the saturated wet weight m3 of the additive manufacturing finished product.

[0076] Specifically, in step S2012, the obtained apparent density ρ1 and bulk density ρ2 of the additive manufacturing finished product satisfy:

[0077] ρ1 = ρ × m1 / (m1 - m2);

[0078] ρ2 = ρ × m1 / (m3 - m2);

[0079] Among them, ρ is the density of the immersion liquid used to obtain m2 and m3 at the test temperature. For ease of operation, deionized water can be selected as the immersion liquid.

[0080] Specifically, in step S202, the obtained total porosity ε1, open porosity ε2, and closed porosity ε3 of the additive manufacturing finished product satisfy:

[0081] ε1 = (1 - ρ2 / ρ0) × 100%;

[0082] ε2 = [(m3 - m1) / (ρ × m1)] ρ2 × 100%;

[0083] ε3 = (ρ2 / ρ1 - ρ2 / ρ0) × 100%;

[0084] Wherein, ρ is the density of the immersion liquid used when obtaining m2 and m3 at the test temperature, ρ1 is the apparent density of the additive manufacturing finished product, ρ2 is the bulk density of the additive manufacturing finished product, and ρ0 is the theoretical density of the material.

[0085] Specifically, the laser scanning power is 100W - 300W, and it can be 100W, 110W, 130W, 140W, 150W, 160W, 170W, 180W, 200W, 230W, 250W, 280W or 300W.

[0086] It should be noted that if the laser scanning power is too small, the energy input is insufficient, which may cause the material to not be completely melted and there are unfused defects. If the laser scanning power is too large, the material absorbs too much energy, and cracks may occur due to excessive thermal stress, etc.

[0087] Specifically, the scanning speed is 900m / s - 1700m / s, and it can be 900m / s, 960m / s, 970m / s, 1000m / s, 1080m / s, 1100m / s, 1120m / s, 1220m / s, 1280m / s, 1320m / s, 1360m / s, 1430m / s, 1480m / s, 1520m / s, 1580m / s, 1610m / s, 1630m / s, 1660m / s or 1700m / s.

[0088] It should be noted that if the scanning speed is too slow, the material is heated for a long time, resulting in coarse grains and affecting the mechanical properties. If the scanning speed is too fast, the material is heated for a short time, and the powder may be completely melted.

[0089] Specifically, the scanning layer thickness is 0.03mm - 0.06mm, and it can be 0.03mm, 0.032mm, 0.036mm, 0.04mm, 0.042mm, 0.045mm, 0.05mm, 0.051mm, 0.054mm, 0.058mm or 0.06mm.

[0090] It should be noted that if the layer thickness is too small, the energy is concentrated, resulting in deformation. If the layer thickness is too large, the powder may not be melted evenly, resulting in unfused defects.

[0091] Preferably, step S2 further includes:

[0092] S203: Plot a two-dimensional coordinate graph of the open porosity ε2, and / or the closed porosity ε3, and / or the total porosity ε1 and the energy density δ to assist in screening the defect-free target samples, where δ satisfies:

[0093] δ = P / (v × h × t);

[0094] P is the laser scanning power, t is the scanning layer thickness, and v is the scanning thickness.

[0095] Specifically, step S203 includes:

[0096] S2031: Construct a two-dimensional plane coordinate system with the open porosity ε2, and / or, the closed porosity ε3, and / or, the total porosity ε1 as the ordinate and δ as the abscissa;

[0097] S2032: Draw a first auxiliary identification line with ε2 = 1% in the coordinate system. The data points in the area below the first auxiliary identification line correspond to the additive manufactured products with ε2 < 1%;

[0098] and / or, draw a second auxiliary identification line with ε3 = 1% in the coordinate system. The data points in the area below the second auxiliary identification line correspond to the additive manufactured products with ε3 < 1%;

[0099] and / or, draw a third auxiliary identification line with ε1 = 2% in the coordinate system. The data points in the area below the third auxiliary identification line correspond to the additive manufactured products with ε1 < 2%;

[0100] S2033: Select the additive manufactured products in the three areas screened in S2032 as the defect-free target samples as needed.

[0101] Preferably, step S2033 includes: taking the intersection of the additive manufactured products in the three areas screened in step S2032 as the defect-free target samples.

[0102] It should be noted that the additive manufactured products that simultaneously satisfy ε2 < 1%, ε3 < 1%, and ε1 < 2% have fewer defects such as crack pores. Using their manufacturing processes to mass-produce products has a lower defect probability and a higher yield rate.

[0103] Compared with the prior art, the present invention takes the intersection of the additive manufactured products that satisfy ε2 < 1%, ε3 < 1%, and ε1 < 2% as the defect-free target samples, further improving the screening accuracy of the defect-free process and reducing the generation of defects.

[0104] Exemplarily, as Figure 1 shown, a two-dimensional coordinate graph with the open porosity, closed porosity, and total porosity as the abscissa and the energy density δ as the ordinate is given. The first auxiliary identification line in red with ε2 = 1%, the second auxiliary identification line in blue with ε3 = 1%, and the third auxiliary identification line in black with ε1 = 2% are used to assist in screening the defect-free target samples.

[0105] On the other hand, the present invention also discloses a titanium alloy additive manufactured product prepared by the above additive manufacturing method.

[0106] To further illustrate the present invention, the following examples and comparative examples are provided:

[0107] Example 1

[0108] This example discloses an additive manufacturing method based on multi-objective constraints of porosity, using titanium alloy TC4 powder, including:

[0109] S1: Prepare additive manufacturing finished products with different process parameters by setting a four-variable orthogonal experiment based on the process parameters of laser scanning power P, scanning speed v, scanning layer thickness t, and scanning spacing h; use the orthogonal experiment method to design the additive manufacturing parameters: laser scanning power - P, scanning speed - v, scanning spacing - h, layer thickness - t.

[0110] The laser scanning power range is 150 - 350 W, with an interval of 50 W; the scanning speed range is 900 - 1700 mm / s, with an interval of 200 mm / s; the scanning spacing range is 0.04 - 0.12 mm, with an interval of 0.02 mm; the layer thickness range is 0.03 - 0.06 mm, with an interval of 0.015 mm; there are a total of 375 groups of data; the size information of the printed sample is 10 mm × 10 mm × 10 mm.

[0111] S2: Select samples with the porosity-related parameters of the finished product ≤ a specific threshold a from the additive manufacturing finished products as defect-free target samples; the porosity-related parameter in step S2 is the closed porosity; the closed porosity ≤ 1%.

[0112] S201: Obtain the apparent density ρ1 and the bulk density ρ2 of the additive manufacturing finished product based on the mass of the additive manufacturing finished product in different moisture content states;

[0113] S2011: Weigh and obtain the dry mass m1 of the additive manufacturing finished product, the floating mass m2 of the additive manufacturing finished product, and the saturated wet mass m3 of the additive manufacturing finished product after drying at 105°C for 2 h;

[0114] Place the additive manufacturing finished product specimen in boiling water for 3 h to fully saturate the specimen, cool to room temperature, and measure the mass of the saturated specimen in the immersion liquid, which is the floating mass m2 of the additive manufacturing finished product.

[0115] Place the additive manufacturing finished product specimen in boiling water for 3 h to fully saturate the specimen, cool to room temperature, wipe off the residual liquid on the surface of the specimen with a cotton cloth saturated with water, and weigh to obtain the saturated wet mass m3 of the additive manufacturing finished product.

[0116] S2012: Obtain the apparent density ρ1 and the bulk density ρ2 of the additive manufacturing finished product based on the dry mass m1 of the additive manufacturing finished product, the floating mass m2 of the additive manufacturing finished product, and the saturated wet mass m3 of the additive manufacturing finished product.

[0117] The apparent density ρ1 of the additive manufacturing finished product and the bulk density ρ2 of the additive manufacturing finished product satisfy:

[0118] ρ1 = ρ × m1 / (m1 - m2);

[0119] ρ2 = ρ × m1 / (m3 - m2).

[0120] S202: Obtain the closed porosity ε3 of the additive manufacturing finished product based on the apparent density ρ1 and the bulk density ρ2; the closed porosity ε3 satisfies:

[0121] ε3 = (ρ2 / ρ1 - ρ2 / ρ0) × 100%.

[0122] S203: Draw a two-dimensional coordinate graph of the closed porosity and the energy density δ to assist in screening the defect-free target samples, and δ satisfies:

[0123] δ = P / (v × h × t).

[0124] S2031: Construct a two-dimensional plane coordinate system with the closed porosity ε3 as the ordinate and δ as the abscissa, as Figure 2 shown;

[0125] S2032:

[0126] Draw a second auxiliary identification line with a closed porosity ε3 = 1% in the coordinate system, and the data points in the area below the second auxiliary identification line correspond to the additive manufacturing finished products with ε3 < 1%;

[0127] S2033: Select the additive manufacturing finished products in three areas screened in S2032 as the defect-free target samples according to needs.

[0128] S3: Batch prepare defect-free additive manufacturing finished products with the process parameters of the target samples as the additive manufacturing process parameters.

[0129] On the premise that the closed porosity ≤ 1%, screen the energy density. There are 25 groups of additive manufacturing forming parameters that meet the closed porosity ≤ 1%. Randomly select the additive manufacturing parameters corresponding to the qualified specimens. For example, when the closed porosity is 0.81%, the energy density is 84.17 J / mm 3 , and at this time, the power, scanning speed, scanning spacing, and layer thickness are (250 W, 1100 mm / s, 0.06 mm, 0.045 mm) respectively. Conduct metallographic characterization on the specimens corresponding to this parameter. There are no obvious visible defects inside the specimens, as Figure 3a shown; there are a small number of pore-like defects on the surface of the specimens, as Figure 3b shown.

[0130] Example 2

[0131] This embodiment discloses an additive manufacturing method based on multi-objective constraints of porosity, using titanium alloy TA6 powder, including:

[0132] S1: Prepare additive manufacturing finished products with different process parameters by setting a four-variable orthogonal experiment based on the process parameters of laser scanning power P, scanning speed v, scanning layer thickness t, and scanning spacing h; use the orthogonal experiment method to design the additive manufacturing parameters: laser scanning power - P, scanning speed - v, scanning spacing - h, layer thickness - t.

[0133] The laser scanning power range is 150 - 350W, with an interval of 50W; the scanning speed range is 900 - 1700mm / s, with an interval of 200mm / s; the scanning spacing range is 0.04 - 0.12mm, with an interval of 0.02mm; the layer thickness range is 0.03 - 0.06mm, with an interval of 0.015mm; there are a total of 375 groups of data; the printed sample size information is 10mm × 10mm × 10mm.

[0134] S2: Select samples with porosity-related parameters ≤ a specific threshold a from the additive manufacturing finished products as defect-free target samples; the porosity-related parameters in step S2 include open porosity, closed porosity, and total porosity at the same time;

[0135] Among them, the open porosity ≤ 1%, the closed porosity ≤ 1%, and the total porosity ≤ 2%.

[0136] S201: Obtain the apparent density ρ1 and the bulk density ρ2 of the additive manufacturing finished product based on the mass of the additive manufacturing finished product under different moisture content states;

[0137] S2011: Weigh and obtain the dry mass m1 of the additive manufacturing finished product, the floating weight m2 of the additive manufacturing finished product, and the saturated wet weight m3 of the additive manufacturing finished product after drying at 105°C for 2h;

[0138] Place the additive manufacturing finished product specimen in boiling water for 3h to fully saturate the specimen, cool to room temperature, and measure the mass of the saturated specimen in the immersion liquid, which is the floating weight m2 of the additive manufacturing finished product.

[0139] Place the additive manufacturing finished product specimen in boiling water for 3h to fully saturate the specimen, cool to room temperature, wipe off the residual liquid on the surface of the specimen with a cotton cloth saturated with water, and weigh to obtain the saturated wet weight m3 of the additive manufacturing finished product.

[0140] S2012: Obtain the apparent density ρ1 and the bulk density ρ2 of the additive manufacturing finished product based on the dry mass m1 of the additive manufacturing finished product, the floating weight m2 of the additive manufacturing finished product, and the saturated wet weight m3 of the additive manufacturing finished product.

[0141] The apparent density ρ1 and the bulk density ρ2 of the additive manufacturing finished product satisfy:

[0142] ρ1 = ρ × m1 / (m1 - m2);

[0143] ρ2 = ρ × m1 / (m3 - m2).

[0144] S202: Obtain the total porosity ε1, open porosity ε2, and closed porosity ε3 of the additive manufacturing finished product based on the apparent density ρ1 and the bulk density ρ2.

[0145] The total porosity ε1, open porosity ε2, and closed porosity ε3 satisfy:

[0146] ε1 = (1 - ρ2 / ρ0) × 100%;

[0147] ε2 = [(m3 - m1) / (ρ × m1)]ρ2 × 100%;

[0148] ε3 = (ρ2 / ρ1 - ρ2 / ρ0) × 100%.

[0149] S203: Plot the two-dimensional coordinate diagrams of the open porosity, closed porosity, total porosity, and energy density δ to assist in screening the defect-free target samples, where δ satisfies:

[0150] δ = P / (v × h × t).

[0151] S2031: Construct a two-dimensional plane coordinate system with the open porosity ε2, closed porosity ε3, and total porosity ε1 as the vertical coordinates and δ as the horizontal coordinate, as shown in Figure 4;

[0152] S2032:

[0153] Draw the first auxiliary identification line with the open porosity ε2 = 1% in the coordinate system. The data points in the area below the first auxiliary identification line correspond to the additive manufacturing finished products with ε2 < 1%;

[0154] Draw the second auxiliary identification line with the closed porosity ε3 = 1% in the coordinate system. The data points in the area below the second auxiliary identification line correspond to the additive manufacturing finished products with ε3 < 1%;

[0155] Draw the third auxiliary identification line with the total porosity ε1 = 2% in the coordinate system. The data points in the area below the third auxiliary identification line correspond to the additive manufacturing finished products with ε1 < 2%;

[0156] S2033: Screen the defect-free target samples from the intersection of the additive manufacturing finished products in the three selected areas.

[0157] S3: Batch prepare defect-free additive manufacturing finished products using the process parameters of the target samples as the additive manufacturing process parameters.

[0158] With the conditions of open porosity ≤ 1%, closed porosity ≤ 1%, and total porosity ≤ 2%, the energy density was screened, and the additive manufacturing parameters corresponding to the maximum total porosity were selected from 5 groups of preferred forming parameters. For example, when the total porosity was 1.74%, the open porosity was 0.84%, and the closed porosity was 0.90%, the energy density was 108.02 J / mm 3 , Figures 4a - 4b At position 001 in Figure 4, at this time, the power, scanning speed, scanning spacing, and layer thickness were (350 W, 900 mm / s, 0.12 mm, 0.03 mm) respectively. Metallographic characterization was carried out on the specimen corresponding to this parameter, and there were no obvious visible defects inside the specimen, such as Figure 5a shown; there were no obvious visible defects on the surface of the specimen, such as Figure 5b .

[0159] The additive manufacturing parameters corresponding to the maximum open porosity that met the conditions were selected. For example, when the open porosity was 0.89%, the closed porosity was 0.74%, and the total porosity was 1.63%, the energy density was 98.04 J / mm 3 , at position 002 in Figure 4, at this time, the power, scanning speed, scanning spacing, and layer thickness were (200 W, 1700 mm / s, 0.04 mm, 0.03 mm) respectively. Metallographic characterization was carried out on the specimen corresponding to this parameter, and there were no obvious visible defects inside the specimen, such as Figure 6a shown; there were no obvious visible defects on the surface of the specimen, such as Figure 6b .

[0160] The additive manufacturing parameters corresponding to the maximum closed porosity that met the conditions were selected. For example, when the closed porosity was 0.94%, the open porosity was 0.53%, and the total porosity was 1.47%, the energy density was 106.06 J / mm 3 , at position 003 in Figure 4, at this time, the power, scanning speed, scanning spacing, and layer thickness were (350 W, 1100 mm / s, 0.1 mm, 0.03 mm) respectively. Metallographic characterization was carried out on the specimen corresponding to this parameter, and there were no obvious visible defects inside the specimen, such as Figure 7a shown; there were no obvious visible defects on the surface of the specimen, such as Figure 7b .

[0161] As can be seen from the above, compared with Example 1, the specimens in this example have fewer defects on the inner and outer surfaces.

[0162] Comparative Example 1

[0163] This comparative example discloses an additive manufacturing method based on multi-objective constraints of porosity. The difference from Example 2 is that a group of data was randomly selected from 375 groups as the target sample without defects, and metallographic analysis was carried out on this sample, and the rest was the same as Example 2.

[0164] Randomly extract the process parameters corresponding to the data: laser scanning power 300W, scanning speed 1100mm / s, scanning pitch 0.10mm, and scanning layer thickness 0.06mm for metallographic characterization. There are certain defects (dark regions) inside the specimen, as Figure 8a shown; there are certain defects on the surface of the specimen, as Figure 8b shown.

[0165] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. An additive manufacturing method based on multi-objective constraints of porosity, characterized in that: The additive manufacturing method based on porosity multi-objective constraints includes: optimizing additive manufacturing process parameters based on porosity-related parameters of the additively manufactured finished product.

2. The additive manufacturing method based on porosity multi-objective constraints according to claim 1, characterized in that: The additive manufacturing method based on porosity multi-objective constraints comprises: S1: Based on the process parameters of laser scanning power P, scanning speed v, scanning layer thickness t, and scanning spacing h, a four-variable orthogonal experiment is set to prepare additive manufacturing products with different process parameters; S2: Screening out samples of the additively manufactured finished products whose porosity-related parameters are ≤ a specific threshold a as defect-free target samples; S3: Using the process parameters of the target sample as the process parameters of additive manufacturing to batch produce defect-free additive manufacturing products.

3. The additive manufacturing method based on porosity multi-objective constraints according to claim 2, characterized in that: The porosity-related parameters in step S2 are open porosity, and / or closed porosity, and / or total porosity.

4. The additive manufacturing method based on porosity multi-objective constraints according to claim 3 is characterized in that: The porosity-related parameter of the finished product in step S2 is less than or equal to a specific threshold a, and satisfies: Open porosity ≤1%, closed porosity ≤1%, total porosity ≤2%.

5. The additive manufacturing method based on porosity multi-objective constraints according to claim 4, characterized in that: Step S2 includes: S201: Obtaining the apparent density ρ1 of the additively manufactured product and the volume density ρ2 of the additively manufactured product based on the mass of the additively manufactured product in a dry state and in a saturated water state based on a boiling method; S202: Based on the apparent density ρ1 and the volume density ρ2, the total porosity ε1, the open porosity ε2, and the closed porosity ε3 of the additively manufactured product are obtained.

6. The additive manufacturing method based on porosity multi-objective constraints according to claim 5, characterized in that: Step S201 includes: S2011: Obtain the mass of the dry additive manufacturing finished product m1, the floating weight of the additive manufacturing finished product m2, and the saturated wet weight of the additive manufacturing finished product m3; S2012: Obtain the apparent density ρ1 of the additive manufacturing product and the volume density ρ2 of the additive manufacturing product based on the mass of the dry additive manufacturing product m1, the floating weight of the additive manufacturing product m2, and the wet weight of the saturated additive manufacturing product m3.

7. The additive manufacturing method based on porosity multi-objective constraints according to claim 6, characterized in that: Step S2 also includes: S203: Draw a two-dimensional coordinate diagram of open porosity, and / or closed porosity, and / or total porosity and energy density δ to assist in screening defect-free target samples, where δ satisfies: δ=P / (v×h×t).

8. The additive manufacturing method based on porosity multi-objective constraints according to claim 7, characterized in that: Step S203 includes: S2031: constructing a two-dimensional plane coordinate system with open porosity ε2, and / or closed porosity ε3, and / or total porosity ε1 as ordinates and δ as abscissas; S2032: Draw a first auxiliary identification line with an open porosity of ε2=1% in the coordinate system, and data points in the area below the first auxiliary identification line correspond to additively manufactured products with ε2<1%; and / or, a second auxiliary identification line with a closed porosity of ε3=1% is drawn in the coordinate system, and data points in the area below the second auxiliary identification line correspond to additively manufactured products with ε3<1%; and / or, a third auxiliary identification line with a total porosity of ε1=2% is drawn in the coordinate system, and data points in the area below the third auxiliary identification line correspond to additively manufactured products with ε1<2%; S2033: Select the additively manufactured products in the three areas screened out in S2032 as defect-free target samples as needed.

9. The additive manufacturing method based on porosity multi-objective constraints according to claim 8, characterized in that: Step S2033 includes: finding the intersection of the additively manufactured products in the three areas screened out in step S2032 as defect-free target samples.

10. A titanium alloy additive manufacturing product, characterized in that: Prepared by the additive manufacturing method according to any one of claims 1 to 9.

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