Parameter optimization method and system for gh4169 alloy
By optimizing the process parameters of selective laser melting, the defect problem in the forming process of nickel-based superalloys was solved, and GH4169 alloy forming parts with high density and excellent mechanical properties were realized, which are suitable for aerospace and other fields.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- TIANJIN SINO GERMAN VOCATIONAL TECHNICAL COLLEGE
- Filing Date
- 2026-05-12
- Publication Date
- 2026-07-31
AI Technical Summary
Traditional manufacturing techniques for processing nickel-based superalloys are characterized by complex processes, high costs, and long cycles. Furthermore, improper process parameters during the SLM forming process can easily lead to internal and external defects, affecting the mechanical properties of the alloy.
By using orthogonal experimental design and polynomial regression analysis, the laser power, scanning speed, and scanning spacing of selective laser melting were optimized, a mathematical model was established, and process parameters were optimized to improve density and mechanical properties.
It achieves high density and good mechanical properties in GH4169 alloy formed parts, reduces defect rate, and meets the needs of high-end equipment in aerospace and other fields.
Smart Images
Figure CN122490813A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of metal additive manufacturing technology, and in particular to a method and system for optimizing the parameters of GH4169 alloy. Background Technology
[0002] Nickel-based superalloys are widely used in aerospace, nuclear power, and petrochemical industries due to their excellent high-temperature strength, corrosion resistance, and fatigue resistance. Among them, GH4169 superalloy, as a precipitation-strengthened nickel-based superalloy, can withstand impact loads and thermal deformation at high temperatures. Traditional manufacturing technologies face numerous bottlenecks in processing nickel-based superalloys, including complex processes, high manufacturing costs, and long delivery cycles, making it difficult to meet the demands of high-end equipment for complex structures, high precision, and integrated high performance.
[0003] Metal additive manufacturing, as a cutting-edge technology, is widely used in aerospace, automotive, shipbuilding, medical and other fields due to its high material utilization rate and rapid development cycle. Selective laser melting (SLM) technology is one of the most promising technologies in additive manufacturing. This process does not require the use of complex supporting facilities such as molds and fixtures. The forming process is simple and is not limited by the geometry of the three-dimensional model. It can form precise and complex structural parts.
[0004] However, SLM technology has only been around for a short time before its industrial application, and it still has some shortcomings. Improper selection of process parameters during the forming process can affect the forming quality of parts, easily leading to internal defects such as spheroidization, cracks, porosity, and lack of fusion, as well as external defects such as cracking, warping, and dimensional abnormalities. These defects severely affect the mechanical properties of nickel-based superalloys. If the laser power is too high, the energy input absorbed by the metal powder per unit time is too high, causing some powder to vaporize and easily producing pores. At the same time, excessive energy input can cause an imbalance in the stability of the molten pool and produce violent fluctuations, leading to splashing of metal powder and molten droplets, causing metallurgical defects such as spheroidization and porosity. Conversely, if the laser power is too low, the input energy cannot meet the requirement for sufficient melting of the metal powder, resulting in structural defects such as keyholes. When the scanning speed is too high, the interaction time between the laser and the metal powder is significantly compressed, resulting in insufficient energy input to meet the powder melting requirements. This not only leads to insufficient penetration depth of the molten pool, making it difficult to achieve complete melting and metallurgical bonding of the powder, but also causes powder splashing due to excessively fast melt flow, resulting in typical defects such as holes and spheroidization inside the formed part. When the scanning speed is too low, the laser dwell time is too long, causing the molten pool to overheat. This not only causes spheroidization defects due to the molten pool adsorbing surrounding powder, but also leads to decreased molten pool stability and molten splashing due to accumulated thermal stress. When the scanning spacing is too small, the high overlap rate leads to a sharp increase in local energy density, causing the molten pool to overheat and forming surface defects such as spherical protrusions. At the same time, the heat accumulation causes remelting of the lower layer, insufficient interlayer filling, and excessive energy causes powder vaporization, resulting in porosity defects such as keyholes. When the spacing is too large, the low overlap rate leads to insufficient energy density, insufficient overlap of the melt channel and insufficient melting of the powder, resulting in defects such as incomplete fusion.
[0005] Therefore, through systematic design of orthogonal experiments and fitting of polynomial regression equations, this study explores the influence and significance ranking of key process parameters such as laser power, scanning speed, and scanning spacing on alloy density. Improving the targeting and efficiency of parameter optimization, and reducing R&D costs and time costs, remains a hot topic that urgently needs to be explored by those skilled in the art. Summary of the Invention
[0006] To address the aforementioned technical problems, this invention provides a quantitative optimization method for process parameters in selective laser melting forming of GH4169 alloy to control density. This invention designs orthogonal experimental groups for the core process parameters of selective laser melting, employs polynomial fitting to perform regression analysis on the experimental data, establishes a quantitative mathematical model between the core process parameters and density, obtains the mathematical relationship between the core process parameters and density, optimizes the process parameters, and analyzes the influence weight of each parameter on the alloy density, resulting in good forming quality of GH4169 alloy with a porosity of less than 0.5%. This technology not only extends the service life of the formed parts but also improves their mechanical properties through parameter optimization. Specifically, it includes the following steps: Step S1: Select the core process parameters of the selective laser melting forming of GH4169 alloy as the process parameters to be optimized and design a factor level table; Step S2: Design orthogonal experimental groups based on the factor level table, and obtain a total of 16 groups of samples after conducting orthogonal experiments; Step S3: The sample is subjected to GH4169 nickel-based high-temperature alloy powder additive manufacturing to obtain the additively manufactured sample; the density of the additively manufactured sample is measured using Archimedes' displacement method. Step S4: Use the polynomial fitting method to perform regression analysis on the process parameters in step S2 and the density data in step S3, establish a quantitative mathematical model between the core process parameters and density, and obtain the mathematical relationship between the core process parameters and density. Step S5: Perform range analysis based on the density data in step S3 to select the optimal parameter combination; Step S6: Substitute the selected optimal parameter combination into the mathematical model obtained in step S4 for verification.
[0007] Furthermore, the core process parameters are laser power, scanning speed, and scanning spacing.
[0008] In step S1, the laser power directly determines the energy input intensity required for powder bed melting, which is crucial for ensuring the quality of interlayer metallurgical bonding. Constructing a reasonable power range (190W-310W) allows for precise control of the energy input intensity, avoiding incomplete melting defects caused by low power and suppressing problems such as molten pool splashing, increased porosity, and thermal stress accumulation caused by high power. The scanning speed directly determines the interaction time between the laser and the alloy powder and the solidification rate of the molten pool. Setting an optimized range of 700mm / s-1300mm / s avoids excessive energy accumulation and low forming efficiency caused by low-speed scanning, while avoiding insufficient energy input, discontinuous molten pool, and spheroidization defects caused by high-speed scanning. The scanning spacing determines the degree of overlap between adjacent molten channels and the integrity of interlayer metallurgical bonding. Setting an optimized range of 0.07mm-0.13mm avoids problems such as excessive accumulation of molten channels, heat input accumulation, and increased surface roughness caused by excessive spacing, while avoiding non-overlapping and porosity defects caused by excessive spacing.
[0009] These three parameters, by controlling the melt channel morphology, melt flowability, and heat input uniformity, achieve a fundamental improvement in surface quality. The scanning spacing precisely matches the melt channel width, ensuring a stable melt channel overlap rate of 80%-90%. The coupled control of laser power and scanning speed regulates the energy density (65 J / mm²). 3 -75J / mm 3This process suppresses melt splashing and spheroidization defects. After optimization, the surface roughness of the formed parts is significantly improved, meeting the surface reference requirements for aerospace components without the need for large-scale machining. Simultaneously, by synergistically controlling the molten pool behavior and metallurgical bonding quality, density is improved. The core mechanisms are: laser power ensures complete melting of the alloy powder, eliminating incomplete fusion porosity; scanning speed controls the molten pool cooling rate, suppressing porosity caused by insufficient gas escape; and scanning spacing ensures continuous overlap of interlayer melt channels, avoiding porosity defects. After optimization, the density of the formed parts reaches 99.5%, close to the theoretical density, laying a solid foundation for improved mechanical properties. The coupling of laser power and scanning speed enables rapid solidification of the molten pool, refining grains and increasing grain boundary strengthening effects; the scanning spacing ensures the integrity of interlayer metallurgical bonding. Optimization results in more stable and reliable mechanical properties of the formed parts.
[0010] Furthermore, the additive manufacturing described in step S3 includes the following steps: Step S301: Construct a 3D model using professional CAD software, export it as an STL format, and use slicing software adapted for metal printing to divide the model into multiple slices, setting the laser power to 190W-310W, the scanning speed to 700mm / s-1300mm / s, and the scanning spacing to 0.07mm-0.13mm. Step S302: After ensuring that the sample powder is dry and free of impurities, place it into the powder feeding cylinder, install the substrate and calibrate the level of the printing platform, fill with inert gas to purge the air, and then start the printing equipment. Step S303: After printing is complete, wait for the working chamber to cool to room temperature, remove the substrate, remove the surface support, and turn off the printer.
[0011] Furthermore, step S3, the measurement of density using the Archimedes' displacement method, includes the following steps: Using deionized water as the medium, an electronic densitometer was used to measure the density. After reading the density value, the density was calculated using the density calculation formula, which is as follows: .
[0012] Furthermore, before measuring the density using the Archimedes displacement method, the additively manufactured sample is pretreated, including ultrasonic cleaning, drying, and vacuum degassing. The ultrasonic cleaning medium is anhydrous ethanol, and the ultrasonic cleaning conditions are 180W-200W ultrasonic cleaning for 15-20 minutes.
[0013] Furthermore, the drying conditions are: 75℃-85℃ for 2-3 hours; the vacuum degassing temperature is 60℃-80℃ for 1-2 hours, and the vacuum degree is ≤10Pa.
[0014] This invention uses anhydrous ethanol for ultrasonic cleaning, which can remove residual unfused powder and processing debris from the surface; drying is carried out in a drying oven, which not only avoids alloy phase transformation, but also ensures that the liquid adsorbed in the pores and on the surface of the sample completely evaporates.
[0015] Furthermore, step S4 specifically includes: Python software was used to perform polynomial fitting on 16 sets of orthogonal experimental data of SLM forming of GH4169 alloy, and a regression equation was established with laser power x1, scanning speed x2, and scanning spacing x3 as independent variables and density y as dependent variable.
[0016] Furthermore, step S5 specifically includes: Calculate the compactness mean K value for each factor level; Subsequently, the range R value of each factor is calculated; Finally, based on the range R value, the significant influence of each factor on the density of GH4169 alloy formed by selective laser melting was determined, and the optimal parameter combination was selected.
[0017] Furthermore, the GH4169 alloy has a particle size of 15μm-53μm.
[0018] Furthermore, the composition of the GH4169 alloy is as follows: Ni: 53.92%; Cr: 18.49%; Nb: 5.18%; Mo: 3.09%; Ti: 1.02%; Al: 0.45%; Co: 0.005%; C: 0.031%; Mn: 0.005%; Si: 0.008%; S: 0.002%; P: 0.005% and the balance Fe.
[0019] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention provides a collaborative parameter optimization method for selective laser melting forming of GH4169 alloy. This method, through the design of a three-factor, four-level orthogonal experiment and fitting with a polynomial regression equation, explores the influence of laser power, scanning speed, and scanning spacing on density, reducing defects such as porosity, cracks, and incomplete fusion in the sample. This provides theoretical basis and data support for production practice and offers a reference for the production and application of GH4169 nickel-based superalloys.
[0020] Meanwhile, by detecting and analyzing the density of the formed parts, the influence weight of the core process parameters on the forming quality was clarified, guiding the targeted optimization of parameters. Attached Figure Description
[0021] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.
[0022] Figure 1 This is a graph showing the effect of laser power on density obtained from range analysis in Example 1; Figure 2 This is a graph showing the effect of scanning speed on packing density obtained from range analysis in Example 1. Figure 3 This is a graph showing the effect of scanning spacing on packing density obtained from range analysis in Example 1. Figure 4 This is a density histogram of the optimal parameter combination obtained from range analysis in Example 1; Figure 5 This is a comparison chart of the true values and fitted values obtained using the polynomial fitting method in Example 2; Figure 6 The graphs shown in Example 2 are the fitting relationships between the core process parameters (laser power, scanning speed, and scanning spacing) obtained by Python software and density. The left graph shows the relationship between laser power and density, the middle graph shows the relationship between scanning speed and density, and the right graph shows the relationship between scanning spacing and density. Figure 7 This is a stress-strain curve obtained from testing with an electronic universal testing machine in Example 3; Figure 8 This is a Vickers hardness histogram obtained by using a micro Vickers hardness tester in Example 4. Detailed Implementation
[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.
[0024] The specific embodiments of the present invention will be described below.
[0025] Example 1 (1) Select the process parameters to be optimized: laser power, scanning speed, and scanning spacing; design a factor level table, see Table 1; Table 1 Factor Level Table (2) The factor levels obtained in step (1) were used to design orthogonal experimental groups, with a total of 16 parameter combinations, as shown in Table 2; Table 2 Orthogonal Experiment Table (3) Print the 16 sets of parameters in step (2) using GH4169 nickel-based high-temperature alloy powder. Construct a three-dimensional model using professional CAD software (such as SolidWorks), export it as STL format, and use slicing software adapted for metal printing (such as Magics) to divide the model into multiple slices. Set the laser power, scanning speed, and scanning spacing parameters. After ensuring that the powder is dry and free of impurities, put it into the powder feeding cylinder, install the substrate and calibrate the level of the printing platform. Fill in inert gas (such as argon) to purge the air and start the printing equipment. After printing is completed, wait for the working chamber to cool to room temperature, remove the substrate, remove the surface support, and turn off the printer. (4) The density of the sample obtained in step (3) is measured using Archimedes' displacement method. First, the sample is ultrasonically cleaned for 20 minutes using an ultrasonic cleaner with anhydrous ethanol as the medium. After cleaning, the sample is dried at 80°C for 2 hours in a drying oven to remove internal pores and residual liquid on the surface; then, vacuum treatment is performed to eliminate internal gas. The pretreated sample needs to be measured by an electronic densitometer. The specific operation process is as follows: First, deionized water is poured into a beaker as the medium and the beaker is placed on the workbench. A double weighing pan system is hung on the instrument hook. The lower weighing pan is immersed in water, while the upper weighing pan is exposed to the air. After pressing the "tare" button, "0.0000g" is displayed on the screen. When the sample to be tested is placed on the upper weighing pan, the mass m1 (in g) of the sample in the air will be displayed on the screen. Then, the sample is taken down and placed on the lower weighing pan immersed in water. It is important to ensure that the sample is completely submerged in water. At this time, m2 displayed on the screen is the mass (in g) of the sample in water. After the values stabilize, press the "Test" button, and the density value of the sample will be displayed directly on the screen. To ensure the accuracy of the measurement results, each molded part is measured three times independently, and the average value is taken as the final result; in this embodiment, the theoretical density value of GH4169 nickel-based superalloy is 8.24 g / cm³. 3 ; (5) Perform range analysis on the packing density measured in step (4) to screen the optimal parameter combination. Range analysis studies the effects of laser power (A), scanning speed (B), and scanning spacing (C) on packing density (ideally, this index should be as large as possible). For each factor, group by "level" and calculate the sum of all experimental indices at that level. Compared with the average ; The sum of all experimental indicators when factor A is at level 1 (A1); Calculation formula (m represents the number of times level A1 occurs); The formula for calculating the range R is: ; (6) Print the sample with the optimal parameter set obtained in step (5) and measure the density; (7) Based on the range analysis results, plot the trend of the density obtained in step (6) as a function of laser power, and see the graph. Figure 1 Based on the range analysis results, the trend of density variation with scanning speed was plotted, see... Figure 2 Based on the range analysis results, the trend of density variation with scanning interval was plotted, see... Figure 3 A density histogram was plotted based on the density measurement results, see [link / reference]. Figure 4 .
[0026] The data in the figure shows that density increases with increasing laser power. Within the laser power range of 190W-310W, as the laser power increases, the energy input to the metal powder per unit time also increases, promoting complete melting of the powder and thus reducing internal porosity and defect formation. Scanning speed also has a significant impact on density. Within the scanning speed threshold of 1100mm / s-1300mm / s, density shows a significant decreasing trend with increasing scanning speed. This is because the laser energy density is insufficient at higher scanning speeds, leading to a decrease in sample density. Within the scanning spacing range of 0.07mm-0.13mm, density decreases with increasing scanning spacing. This is because an excessively large scanning spacing reduces the overlap between laser beams, causing some areas of powder to not be fully melted, thus affecting the sample density.
[0027] Example 2 Polynomial fitting regression equation The density obtained by Archimedes' displacement method in Example 1 is taken.
[0028] (1) The independent variables (experimental factors) and dependent variables (experimental results) of 16 orthogonal experiments were read using the pandas library of Python software.
[0029] (2) Use the PolynomialFeatures module in the sklearn library of Python to generate a second-order polynomial feature matrix, and combine it with the regression model to construct a second-order polynomial fitting equation, where the independent variables are the influencing factors of the orthogonal experiment and the dependent variable is the experimental result.
[0030] (3) Using the model's coefficient of determination (R²) 2Using the maximum value as the screening criterion, the polynomial fitting equations are sorted to determine the target fitting equation with the highest accuracy, and its complete expression is recorded: Fitting R 2 Score: 0.9676.
[0031] (4) Substitute the optimal parameter combination into the fitting equation and control the error within 2% to achieve the expected result.
[0032] A comparison chart of the true values and fitted values obtained through the polynomial fitting method can be found below. Figure 5 The fitting relationship between the core process parameters (laser power, scanning speed, scanning spacing) and density obtained from Python software is shown in the figure. Figure 6 The left figure shows the relationship between laser power and density, the middle figure shows the relationship between scanning speed and density, and the right figure shows the relationship between scanning spacing and density.
[0033] Example 3 Tensile property test The parameter set obtained from the optimization in Example 1 is used.
[0034] (1) Print the sample according to the optimized parameter set. Construct a 3D block model with a size of 60mm×10mm×5mm using professional CAD software (SolidWorks), export it as STL format, and use slicing software (Magics) adapted for metal printing to divide the model into multi-layer slices. Set the laser power, scanning speed and scanning spacing parameters. After ensuring that the powder is dry and free of impurities, put it into the powder feeding cylinder, install the substrate and calibrate the level of the printing platform. Fill in inert gas (argon) to purge the air and start the printing equipment. After printing is completed, wait for the working chamber to cool to room temperature, take out the substrate, remove the surface support, and turn off the printer.
[0035] (2) The printed specimens were cut into standard tensile specimens using a wire EDM machine; tensile tests were performed using an electronic universal testing machine, and stress-strain curves were plotted based on real-time data. The test results are as follows: Figure 7 As shown.
[0036] As can be seen from the data in the figure, the elongation after fracture of the sample is 40.8% and the reduction of area is 49.8%. The elongation after fracture in the printed state is higher than the 30% elongation obtained by traditional processing, and the reduction of area is also at the upper limit of the data range obtained by traditional manufacturing.
[0037] Example 4 Vickers hardness test The parameter set obtained from the optimization in Example 1 is used.
[0038] (1) Print the sample according to the optimized parameter set. Construct a 3D block model with a size of 10mm×10mm×10mm using professional CAD software (such as SolidWorks), export it as STL format, and use slicing software adapted for metal printing (such as Magics) to divide the model into multiple slices. Set the laser power, scanning speed and scanning spacing parameters. After ensuring that the powder is dry and free of impurities, put it into the powder feeding cylinder, install the substrate and calibrate the level of the printing platform. Fill in inert gas (such as argon) to purge the air and start the printing equipment. After printing is completed, wait for the working chamber to cool to room temperature, take out the substrate, remove the surface support, and turn off the printer.
[0039] (2) The Vickers hardness was measured using a Huayin HV-1000A Vickers hardness tester at room temperature. The load was 100g and the holding time was 15s. Twelve test points were selected sequentially along the vertical line in the center area of the sample, and the distance between two points had to be greater than three times the diagonal distance of the indentation. The highest and lowest hardness values were removed, and the average value of the ten valid data points was selected and determined as the final hardness characterization value of the sample. The test results are as follows: Figure 8 As shown.
[0040] In summary, the SLM forming process parameters for GH4169 alloy have varying degrees of control over the sample density, with the energy density set between 20-80 J / mm². 3 Within the specified range, the order of influence of various process parameters on packing density is: scanning spacing > laser power > scanning speed. The optimal parameter combination is a laser power of 310W, a scanning speed of 700mm / s, and a scanning spacing of 0.07mm. Energy density ≥ 62J / mm². 3 The density of the samples was all above 95%, with an energy density of 73.02 J / mm². 3 The sample density reached a peak of 99.9%.
[0041] Room temperature tensile properties: Elongation at break reaches 40.8%, and reduction of area reaches 49.8%, which are higher than the conventional levels of traditional forgings. Tensile strength is 794.3 MPa, and yield strength is 501.02 MPa, which are below the upper limit of forgings. Room temperature impact properties: Impact energy and impact toughness reach the upper limit of traditional cast and forged alloys. The impact fracture surface exhibits typical ductile fracture characteristics: a large number of dimples are distributed in both the edge and central regions of the fracture surface, and the dimples are more dense in the edge region, indicating that the material has good room temperature impact toughness.
[0042] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.
Claims
1. A method for quantitative optimization of process parameters for density control in selective laser melting forming of GH4169 alloy, characterized in that, Includes the following steps: Step S1: Select the core process parameters of the selective laser melting forming of GH4169 alloy as the process parameters to be optimized and design a factor level table; Step S2: Design orthogonal experimental groups based on the factor level table, and obtain a total of 16 groups of samples after conducting orthogonal experiments; Step S3: The sample is subjected to GH4169 nickel-based high-temperature alloy powder additive manufacturing to obtain the additively manufactured sample; the density of the additively manufactured sample is measured using Archimedes' displacement method. Step S4: Use the polynomial fitting method to perform regression analysis on the process parameters in step S2 and the density data in step S3, establish a quantitative mathematical model between the core process parameters and density, and obtain the mathematical relationship between the core process parameters and density. Step S5: Perform range analysis based on the density data in step S3 to select the optimal parameter combination; Step S6: Substitute the selected optimal parameter combination into the mathematical model obtained in step S4 for verification.
2. The method for quantitative optimization of process parameters for density control in selective laser melting forming of GH4169 alloy according to claim 1, characterized in that, The core process parameters are laser power, scanning speed, and scanning spacing.
3. The method for quantitative optimization of process parameters for density control in selective laser melting forming of GH4169 alloy according to claim 1, characterized in that, Step S3 of the additive manufacturing process includes the following steps: Step S301: Construct a 3D model using professional CAD software, export it as an STL format, and use slicing software adapted for metal printing to divide the model into multiple slices, setting the laser power to 190W-310W, the scanning speed to 700mm / s-1300mm / s, and the scanning spacing to 0.07mm-0.13mm. Step S302: After ensuring that the sample powder is dry and free of impurities, place it into the powder feeding cylinder, install the substrate and calibrate the level of the printing platform, fill with inert gas to purge the air, and then start the printing equipment. Step S303: After printing is complete, wait for the working chamber to cool to room temperature, remove the substrate, remove the surface support, and turn off the printer.
4. The method for quantitative optimization of process parameters for density control in selective laser melting forming of GH4169 alloy according to claim 1, characterized in that, Step S3, measuring density using the Archimedes displacement method, includes the following steps: Using deionized water as the medium, an electronic densitometer was used to measure the density. After reading the density value, the density was calculated using the density calculation formula, which is as follows: 。 5. The method for quantitative optimization of process parameters for density control in selective laser melting forming of GH4169 alloy according to claim 4, characterized in that, Before measuring the density using the Archimedes displacement method, the additively manufactured sample is pretreated, including ultrasonic cleaning, drying, and vacuum degassing. The ultrasonic cleaning medium is anhydrous ethanol, and the ultrasonic cleaning conditions are 180W-200W ultrasonic cleaning for 15-20 minutes.
6. The method for quantitative optimization of process parameters for density control in selective laser melting forming of GH4169 alloy according to claim 5, characterized in that, The drying conditions are: 75℃-85℃ for 2-3 hours; the vacuum degassing temperature is 60℃-80℃ for 1-2 hours, and the vacuum degree is ≤10Pa.
7. The method for quantitative optimization of process parameters for density control in selective laser melting forming of GH4169 alloy according to claim 1, characterized in that, Step S4 specifically involves: Python software was used to perform polynomial fitting on 16 sets of orthogonal experimental data of SLM forming of GH4169 alloy, and a regression equation was established with laser power x1, scanning speed x2, and scanning spacing x3 as independent variables and density y as dependent variable.
8. The method for quantitative optimization of process parameters for density control in selective laser melting forming of GH4169 alloy according to claim 1, characterized in that, Step S5 specifically involves: Calculate the compactness mean K value for each factor level; Then, the range R value of each factor was calculated; Finally, based on the range R value, the significant influence of each factor on the density of GH4169 alloy formed by selective laser melting was determined, and the optimal parameter combination was selected.
9. The method for quantitative optimization of process parameters for density control in selective laser melting forming of GH4169 alloy according to claim 1, characterized in that, The GH4169 alloy has a particle size of 15μm-53μm.
10. The method for quantitative optimization of process parameters for density control in selective laser melting forming of GH4169 alloy according to claim 1, characterized in that, The composition of the GH4169 alloy is as follows: Ni: 53.92%; Cr: 18.49%; Nb: 5.18%; Mo: 3.09%; Ti: 1.02%; Al: 0.45%; Co: 0.005%; C: 0.031%; Mn: 0.005%; Si: 0.008%. S：0.002%； P: 0.005% and balance Fe.