Surface roughness prediction method for selective laser melting additive manufacturing part

Abstract

The invention discloses a surface roughness prediction method for a selective laser melting additive manufacturing part, and belongs to the technical field of additive manufacturing. According to the method, different roughness prediction models are constructed for the first time according to the relation between the inclination direction of a printed workpiece and the scraping direction of a scraper; the prediction precision of the surface roughness of the workpiece prepared by the SLM process is improved, and the constructed model is a polynomial model. Compared with a traditional model, on one hand, the model considers the change relation of the surface roughness along with the inclination direction under the two conditions of forward scraping and reverse scraping, and the prediction precision is improved; on the other hand, compared with a traditional linear model, fitting of the nonlinear relation is enhanced through the model; compared with an artificial neural network and other black-box nonlinear prediction models, the model has an explicit interpretable expression, and can be directly applied by engineers conveniently. The method has certain universality and is suitable for different SLM printing process parameters, printing shapes and printing materials.

Description

Technical Field

[0001] The invention belongs to the technical field of metal selective laser melting additive manufacturing, and relates to a method for predicting the surface roughness of a selective laser melting additive manufacturing part. Background Art

[0002] Selective laser melting (SLM) is an advanced additive manufacturing technology that produces metal parts of complex shapes by depositing metal powder layer by layer, melting it with laser and rapidly cooling it. Due to its irreplaceable advantages in material processing and structural design, it has been widely used in key industrial fields such as aviation, aerospace and automobile manufacturing, and has become a new research hotspot in the field of structural-functional integrated manufacturing of metal materials.

[0003] Different placement strategies for additively manufactured three-dimensional parts make the surface of the parts present different inclinations relative to the horizontal substrate. For the inclined plate of the formed workpiece, the following effects will be brought about during the SLM forming process: 1) The gravity of the upper material and the support of the material on the surface with different inclination angles will cause different stresses due to the rapid cooling of the material during the additive manufacturing process; 2) The degree of "step effect" caused by slicing on the surface with different inclination angles is different. The above situation will cause the difference in surface roughness of different inclination angles, thereby affecting the surface quality of the printed parts. Therefore, it is particularly important to monitor and predict the surface quality of SLM parts with different inclination angles.

[0004] At present, domestic and foreign scholars have conducted experimental quantitative tests and statistical analysis on the inclination angle and surface roughness of printed workpieces, and obtained qualitative or simple quantitative relationships. However, since there is not a single linear relationship between the surface roughness of different materials and the inclination angle of the inclined plane, a simple linear model cannot be accurately fitted. Therefore, the existing methods still have problems such as low accuracy and poor applicability, and cannot be directly applied to the surface roughness prediction of different metal material parts in actual SLM forming. Summary of the invention

[0005] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and provide a surface roughness prediction method for selective laser melting additively manufactured parts to solve the problems of low surface roughness prediction accuracy and poor applicability of existing additively manufactured parts.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions: A method for predicting the surface roughness of a part manufactured by selective laser melting additive manufacturing comprises the following steps: Step 1, design two groups of inclined plate models in the simulation software, each group of inclined plate models includes a number of inclined plates with the same inclined direction; the inclined direction of the inclined plates in one group of inclined plate models is the same as the direction of the scraper spreading the powder, and the inclined direction of the inclined plates in another group of inclined plate models is opposite to the direction of the scraper spreading the powder; Step 2, by selective laser melting, printing materials according to two groups of inclined plate models to obtain two groups of inclined workpieces, namely, a forward scraper inclined workpiece group and a reverse scraper inclined workpiece group; Step 3, separating the inclined workpiece from the substrate, and measuring and calculating the upper inclined surface roughness and the lower inclined surface roughness of all the inclined workpieces; Step 4, based on the roughness of the upper inclined surface and the roughness of the lower inclined surface in the workpiece group tilted with the scraper, a mathematical relationship between the inclination angle of the inclined surface and the surface roughness in the workpiece group tilted with the scraper; based on the roughness of the upper inclined surface and the roughness of the lower inclined surface in the workpiece group tilted with the reverse scraper, a mathematical relationship between the inclination angle of the inclined surface and the surface roughness in the workpiece group tilted with the reverse scraper is constructed to obtain two groups of roughness prediction models; Step 5: When the inclined workpiece of the same material is printed by selective laser melting, the roughness of the printed inclined workpiece is predicted by the corresponding roughness prediction model.

[0007] A further improvement of the present invention is: Preferably, in step 1, in the same group of inclined plate models, the inclination angles of the inclined plates are different.

[0008] Preferably, in the same set of inclined plate models, the angle between the upper inclined surface and the horizontal base plate, and the angle between the lower inclined surface and the horizontal base plate are 20-55°.

[0009] Preferably, in step 3, the inclined workpiece is separated from the substrate by wire cutting.

[0010] Preferably, in step 3, the upper inclined surface is an inclined surface whose angle between the surface normal vector and the positive direction of the forming direction is an acute angle; the lower inclined surface is an inclined surface whose angle between the surface normal vector and the positive direction of the forming direction is an obtuse angle.

[0011] Preferably, in step 3, the roughness of the upper inclined surface and the lower inclined surface is measured by a laser confocal optical microscope, and the magnification of the microscope is 1000 times.

[0012] Preferably, in step 3, for the same plane, an average value of the lateral roughness measured several times and the longitudinal roughness measured several times is calculated as the roughness of the measured inclined surface.

[0013] Preferably, in step 4, the mathematical fitting process is to mathematically fit the upper inclined surface roughness and the lower inclined surface roughness obtained in step 3 for the same group of inclined workpieces by the least squares method to obtain a polynomial, which is the roughness prediction model for the same group of inclined workpieces.

[0014] Preferably, the highest degree of the polynomial is 2.

[0015] Preferably, in step 5, the printing direction and the direction of the scraper spreading powder are determined based on the roughness prediction result of the inclined workpiece to be printed and the roughness requirement of the inclined workpiece to be printed.

[0016] Compared with the prior art, the present invention has the following beneficial effects: The present invention discloses a method for predicting the surface roughness of a part manufactured by selective laser melting additive manufacturing. The method first finds that the inclination direction and inclination angle of the inclined surface of the printed inclined workpiece and the direction of the scraper powder spreading are related to the surface roughness of the printed inclined workpiece during SLM printing, and establishes two surface roughness prediction models in the forward / reverse scraper directions, respectively. Compared with the existing prediction methods, the accuracy of the SLM surface roughness prediction is improved. In addition, the present invention establishes a nonlinear mapping relationship between the surface inclination angle and the surface roughness based on a polynomial model, and proposes an explicit prediction model. On the one hand, compared with the traditional linear model, the model enhances the fitting of the nonlinear relationship; on the other hand, compared with the black box nonlinear prediction models such as artificial neural networks, the model can provide an explicit and interpretable expression to guide the application of the present invention by engineers; and the method has a certain universality. For different SLM printing process parameters, printing shapes and printing materials, the corresponding prediction model can be determined through the early printing setting test, so that the model is more targeted and has high accuracy when applied. Therefore, the method of the present invention has unique advantages in the application of surface roughness prediction of selective laser melting additive manufacturing. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 Flowchart of the method for rapid and accurate prediction of surface roughness of SLM parts.

[0018] Figure 2 The CAD models of inclined plates with different inclination angles and placed in the same or opposite direction of the scraper. Among them: (a) An example of an inclined plate CAD model with an angle of 55° and its upper inclined surface; (b) The lower inclined surface of the CAD model of an inclined plate with an angle of 55°; (c) The CAD models of inclined plates with different inclination angles placed in the same or opposite direction of the scraper powder spreading.

[0019] Figure 3 The forming conditions of the inclined plate parts obtained after cutting from the substrate after SLM printing contact; among them: (a) the inclined plate is placed in the same direction as the scraper powder spreading direction; (b) the inclined plate is placed in the opposite direction as the scraper powder spreading direction.

[0020] Figure 4The morphology and roughness of the inclined surface were obtained by using a laser confocal microscope. Among them: (a) the upper inclined surface of the 25° forward inclined plate; (b) the lower inclined surface of the 25° forward inclined plate; (c) the inclined surface of the 25° reverse inclined plate; (d) the lower inclined surface of the 25° reverse inclined plate.

[0021] Figure 5 The roughness curve of the upper and lower inclined surfaces with different forward / reverse scraper directions varies with the angle. The dotted line represents the lower inclined surface, the solid line represents the upper inclined surface, the red line represents the forward scraper powder spreading direction, and the blue line represents the reverse scraper powder spreading direction.

[0022] Figure 6 The two curves of surface roughness scatter points in the forward / reverse scraper direction and their quadratic polynomial fitting in the θ space formed by the inclined plane and the horizontal plane. Among them: red represents the forward scraper powder spreading direction, and blue represents the reverse scraper powder spreading direction. DETAILED DESCRIPTION

[0023] The present invention is further described in detail below in conjunction with the accompanying drawings: In the description of the present invention, it should be noted that the orientations or positional relationships indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inside", "outside", etc. are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention; the terms "first", "second", and "third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance; in addition, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection or a detachable connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the internal communication of two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0024] The present invention discloses a method for quickly and accurately predicting the surface roughness of a part manufactured by selective laser melting additive manufacturing, comprising the following steps: Step 1, design two groups of inclined plate models with different inclination angles in the simulation software, one group is placed in the forward scraper spreading direction (referred to as forward scraper placement), and the other group is placed in the reverse scraper spreading direction (referred to as reverse scraper placement), to obtain two groups of inclined plate models, each group of inclined plate models includes several inclined plates with the same inclination direction.

[0025] Step 2, select the printing powder material, determine the printing equipment and process parameters, and perform SLM printing; obtain two groups of inclined workpieces, namely, a forward scraper inclined workpiece group and a reverse scraper inclined workpiece group.

[0026] Step 3, cutting the printed inclined plates with different inclination angles from the substrate by wire cutting method, measuring the roughness of the upper inclined surface and the lower inclined surface of all inclined workpieces, and collecting and collating the data; Step 4, based on the roughness of the upper inclined surface and the lower inclined surface in the group of workpieces tilted with the scraper, construct a mathematical relationship between the inclination angle of the inclined surface and the surface roughness in the group of workpieces tilted with the scraper; based on the roughness of the upper inclined surface and the lower inclined surface in the group of workpieces tilted with the reverse scraper, construct a mathematical relationship between the inclination angle of the inclined surface and the surface roughness in the group of workpieces tilted with the reverse scraper, and the fitting method is the least squares method to obtain two sets of polynomials, which are the mapping relationship between the inclination angle of the inclined surface and the surface roughness, and obtain the inclined surface roughness prediction model of the workpiece tilted with the scraper and the inclined surface roughness prediction model of the workpiece tilted with the reverse scraper.

[0027] Step 5, using the printing equipment and process parameters in step 2 to print parts made of the same material, the roughness of each surface unit can be calculated using the roughness prediction model in step 4 according to the relative relationship between each surface unit of the part and the scraper movement direction (forward or reverse) and the tilt direction of the surface during the printing process; the average roughness of the entire part product can be obtained by taking the average; or the surface roughness of the key surface of the part that affects the target performance can be calculated separately.

[0028] In some embodiments of the present invention, in step 1, each inclined plate in each set of inclined plate models is defined as a cube with a certain inclination angle, the top surface is a horizontal plane, and the model height varies with the inclination angle. The placement direction in which the inclination direction of the inclined surface is consistent with the direction of the scraper spreading powder is defined as placement in the direction of the scraper, and vice versa.

[0029] It should be understood that in step 1, the inclination values ​​of multiple inclined plates in the same set of inclined plate models can be different, and the inclination angles in each set of inclined plate models can be set with denser steps to make the data richer and enhance the accuracy of the entire model.

[0030] For the same inclined plate, the inclined surface whose surface normal vector and the positive angle of the forming direction are acute is defined as the upper inclined surface, and the inclined surface whose surface normal vector and the positive angle of the forming direction are obtuse is defined as the lower inclined surface.

[0031] It should be noted that, for the same inclined plate, the angle between the upper inclined surface and the substrate and the angle between the lower inclined surface and the substrate can be the same or different, and can be set specifically according to the target forming shape of the final printed workpiece; however, the results can be used to construct the final roughness prediction model.

[0032] As a preferred solution, in the same set of inclined plate models, the angle between the upper inclined surface and the horizontal substrate, and the angle between the lower inclined surface and the horizontal substrate are 20-55°, which are mostly the actual workpiece inclination angles. Further, the angles can be adjusted according to the actual printing conditions.

[0033] The above-mentioned setting method of the printing model enables the method to be applicable to constructing roughness prediction models of various workpieces to be printed.

[0034] In some embodiments of the present invention, in step 2, the powder material, printing equipment and process parameters are not restricted, as long as the material composition and each SLM printing parameter in the same batch used for modeling remain consistent; in the actual modeling process, the powder material, printing equipment and process parameters are consistent with the workpiece of the subsequent surface roughness process that needs to be predicted.

[0035] In some embodiments of the present invention, in step 3, a laser confocal optical microscope is used to capture the surface roughness Ra at 1000 times, and the average of 5 transverse Ra and 5 longitudinal Ra is calculated as the surface roughness Ra value of the surface. Specifically, transverse Ra refers to the microscopic unevenness of the part surface in the transverse direction (i.e., perpendicular to the tool cutting direction). Longitudinal Ra refers to the microscopic unevenness of the part surface in the longitudinal direction (i.e., parallel to the tool cutting direction). Considering the measurement of transverse Ra and longitudinal Ra at the same time, and considering multiple measurement values, the roughness of each inclined surface can be made more representative.

[0036] In some embodiments of the present invention, in step 4, the maximum order of polynomial model fitting is selected as 2, and the upper / lower inclined surface roughness values ​​in the forward / reverse scraper direction are respectively brought into the model to fit the coefficients and intercept sizes, so that the prediction model is expressed in the form of a display equation.

[0037] The range of the inclined plate angle discussed in step 1 is 0°~90°, and the experiment needs to be divided into two cases: forward and reverse scraping. Each case corresponds to four cases of upper inclined surface and lower inclined surface, which is not convenient for the practical application of SLM additive manufacturing. In order to achieve unified analysis and quantitative prediction of the roughness of all upper / lower inclined surfaces, the angle between the surface vector of the upper / lower inclined surface and the horizontal vector is defined as θ, and the relationship between the surface roughness and θ is quantitatively discussed, as shown in the attached figure. Figure 6 As shown. The value range of θ is 0°~180°, where 90°<θ<180° and 0°<θ<90° respectively represent the angles between the upper / lower inclined surface and the horizontal substrate. The blue points are in the reverse direction of the scraper, and the red points are in the forward direction of the scraper.

[0038] Furthermore, based on the least squares method, the quadratic polynomial calculation formula for surface roughness was fitted to the forward scraper / reverse scraper roughness results respectively.

[0039] By fitting, the surface roughness of the scraper The calculation formula is:

[0040] in, , are the coefficients of the quadratic and linear terms, respectively. is a constant term.

[0041] Surface roughness of reverse scraper The calculation formula is:

[0042] in, , are the coefficients of the quadratic and linear terms, respectively. is a constant term.

[0043] It should be understood that the two roughness prediction models constructed in the above process correspond to the model corresponding to the forward scraper placement and the model corresponding to the reverse scraper placement, respectively. Through the roughness measurement data of different models, models corresponding to different printing directions are constructed for prediction. The model corresponding to the same printing direction can simultaneously predict the roughness of the upper inclined surface and the lower inclined surface of a printed workpiece.

[0044] Furthermore, through this method, in actual SLM, after determining the placement and forming method of the parts, the inclination angle θ of the inclined surface of the different surfaces in the part model can be brought into different prediction models for the forward / reverse scraper direction, and the roughness of the surface can be predicted, thereby achieving quantitative and accurate prediction of the roughness of all surfaces of the entire part. The printing direction can also be determined based on the roughness prediction results and the roughness of the target part to be printed, so that the roughness of the final prepared part can meet the requirements.

[0045] The following is further described in conjunction with specific embodiments.

[0046] Example 1 Step 1: Design and place the three-dimensional drawing of the inclined plate parts.

[0047] Based on UG 3D software, design the inclined plate part model with different inclination angles. Here, "inclination angle" is defined as the angle between the inclined surface of the inclined plate and the horizontal plane (taking a positive acute angle). Design the inclined plate model as an inclined cube, and define the inclined surface with an acute angle between the surface normal vector and the positive angle of the forming direction as the upper inclined surface, and the inclined surface with an obtuse angle between the surface normal vector and the positive angle of the forming direction as the lower inclined surface, as shown in the attached figure. Figure 2As shown in (a) and (b) in the figure, the bottom and top surfaces remain horizontal, with lengths and widths of 30 mm and 10 mm respectively, and the length of the inclined plane is 30 mm; the two side surfaces remain vertical, and the two inclined planes are inclined, with an inclination angle ranging from 20° to 55°, a step length of 5°, and a fixed length of 30 mm. The height of the inclined plate will decrease as the inclination angle decreases. In summary, a total of 8 inclined plate models with different inclination angles were designed.

[0048] Based on Magcis software, the printing positions and directions of the inclined plate models with different inclination angles are placed on the virtual SLM printing platform, as shown in the attached figure. Figure 2 As shown in (c) in the figure. The placement direction in which the inclined surface is in line with the scraper powder spreading direction is defined as the forward scraper powder spreading direction placement, and vice versa. On the virtual platform of Magcis software, in order to explore the effect of different forward / reverse scraper directions on surface roughness, 8 inclined plate models were placed once in the forward direction and once in the reverse direction. In summary, a total of 16 inclined plate models were subjected to the subsequent SLM additive manufacturing.

[0049] Step 2: SLM additive manufacturing of the inclined plate model.

[0050] In this example, AlSi10Mg is used as an example material to verify the method of the present invention.

[0051] In step 2.1, AlSi10Mg powder with a particle size of 15-53 μm was selected. The measured element contents were: Si 10.14%, Mg 0.31%, Fe 0.062%, H 0.0017%, O 0.044%, Pb and Sn contents were all <0.02%, Cu, Mn, Ni, Zn, and Ti contents were all <0.01%, N content was less than 0.002%, and the balance was Al.

[0052] Step 2.2, the SLM printing equipment used in this case is the BLT-S320. Put the powder into the powder supply cabin of the SLM printer and start printing. The physical laser process parameters are designed as follows: laser power 340 W, scanning speed 1400 mm / s, scanning spacing 0.13 mm, and forming layer height 0.03 mm. The scanning strategy selects strip scanning, the overlap rate is 0.02 mm, the rotation angle between adjacent layers is 67°, and the substrate is preheated to 80°C.

[0053] Step 2.3, after printing, use wire cutting to separate the inclined plate sample from the substrate.

[0054] Step 3: Compare the forming conditions of the inclined plates placed in different forward / reverse scraper directions Step 3.1, arrange the inclined plates in different directions of the scraper spreading powder, as shown in the attached figure Figure 3As shown in (a) and (b) in the figure, it can be found that the forming can still be achieved when the inclined plate inclination angle is 30° in the direction of the scraper, and the forming fails when the inclined plate inclination angle is lower than 30°; while the forming fails when the inclined plate inclination angle is 30° in the direction of the reverse scraper, which indicates that the forming limit inclination angle in the direction of the scraper is larger than that in the direction of the reverse scraper.

[0055] Step 3.2, using a laser confocal optical microscope at 1000 times magnification to capture the roughness Ra of the upper and lower inclined surfaces of 16 inclined plates, and calculating the average of the lateral Ra and longitudinal Ra of 5 times as the surface roughness Ra value of the surface. Taking the inclined plate with an inclination angle of 25° as an example, the organization diagrams of different forward / reverse scraper directions and different upper and lower inclined surfaces and the schematic diagram of the surface roughness with better visualization effect are compared, as shown in the attached figure Figure 4 As shown in (a)-(d) in the figure. It can be found that for the same upward inclined surface, the upper inclined surface in the direction of the scraper is similar to the upper inclined surface in the direction of the reverse scraper. Clear transverse molten pool stripes can be seen from the organizational diagram, and the peak values ​​of the surface roughness are similar, but the surface roughness in the direction of the reverse scraper is more fluctuating than that in the direction of the scraper. For the same downward inclined surface, the surface roughness of the downward inclined surface in the direction of the scraper is significantly lower than that in the direction of the reverse scraper. The peak value difference of the surface roughness is large, the fluctuation of the surface roughness in the direction of the reverse scraper is larger, and the roughness peak of the spheroidized protrusion is sharper. In addition, regardless of whether it is in the direction of the scraper or the scraper, the roughness of the upper inclined surface is significantly lower than that of the lower inclined surface, and the forming quality of the lower inclined surface is worse. The statistics of the roughness of the inclined plates in the direction of the scraper / reverse scraper and the upper / lower inclined surfaces of all inclination angles are shown in the attached figure. Figure 5 As shown, this indicates that, despite the same inclination angle, the forming surface quality of the inclined plate placed along the scraper direction is better than that of the inclined plate placed against the scraper direction. Among them, the forming quality of the upper inclined surfaces of the two is relatively close, while the forming quality of the lower inclined surfaces is quite different.

[0056] Step 4: Establish a surface roughness prediction model in the forward / reverse scraping direction.

[0057] Step 4.1, the current design of the inclined plate inclination angle discussion ranges from 0° to 90°, and needs to be divided into four cases of up / down inclined surface and forward / reverse scraper for classification and discussion, which is not convenient for the practical application of SLM additive manufacturing. In order to achieve unified analysis and quantitative prediction of the roughness of all up / down inclined surfaces, the angle between the surface vector of the up / down surface and the horizontal vector is defined as θ, and the relationship between the surface roughness and θ is quantitatively discussed, as shown in the attached figure Figure 6 As shown. The value range of θ is 0°~180°, where 90°<θ<180° and 0°<θ<90° represent the upper / lower inclined surface conditions, respectively. The blue points are in the reverse direction of the scraper, and the red points are in the same direction of the scraper.

[0058] Step 4.2, based on the least squares method, fit the surface roughness quadratic polynomial calculation formula for the forward scraper / reverse scraper roughness results respectively.

[0059] By fitting, the surface roughness of the workpiece is adjusted along the scraper tilt The calculation formula is:

[0060] Its determination coefficient R 2 The value is 0.75 and the root mean square error RMSE is 3.56, which shows that the fitted formula has high prediction accuracy.

[0061] Surface roughness of workpiece with reverse scraper tilt The calculation formula is:

[0062] Its determination coefficient R 2 The value is 0.93 and the root mean square error RMSE is 2.33, which shows that the fitted formula has high prediction accuracy.

[0063] Finally, for the target part model, after determining the forward / reverse scraper direction and its inclination angle θ of the patch unit, and substituting them into the above two equations, the quantitative and accurate prediction of the surface roughness of the entire part can be achieved.

[0064] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for predicting the surface roughness of a part manufactured by selective laser melting additive manufacturing, characterized in that: The following steps are involved: Step 1, design two groups of inclined plate models in the simulation software, each group of inclined plate models includes a number of inclined plates with the same inclined direction; the inclined direction of the inclined plates in one group of inclined plate models is the same as the direction of the scraper spreading the powder, and the inclined direction of the inclined plates in another group of inclined plate models is opposite to the direction of the scraper spreading the powder; Step 2, by selective laser melting, printing materials according to two groups of inclined plate models to obtain two groups of inclined workpieces, namely, a forward scraper inclined workpiece group and a reverse scraper inclined workpiece group; Step 3, separating the inclined workpiece from the substrate, and measuring and calculating the upper inclined surface roughness and the lower inclined surface roughness of all the inclined workpieces; Step 4, based on the roughness of the upper inclined surface and the roughness of the lower inclined surface in the forward scraper inclined workpiece group, a mathematical relationship between the inclination angle of the inclined surface and the surface roughness in the forward scraper inclined workpiece group is constructed; based on the roughness of the upper inclined surface and the roughness of the lower inclined surface in the reverse scraper inclined workpiece group, a mathematical relationship between the inclination angle of the inclined surface and the surface roughness in the reverse scraper inclined workpiece group is constructed to obtain two groups of roughness prediction models; Step 5: When the inclined workpiece of the same material is printed by selective laser melting, the roughness of the printed inclined workpiece is predicted by the corresponding roughness prediction model.

2. The surface roughness prediction method of a selective laser melting additively manufactured part according to claim 1, characterized in that: In step 1, in the same set of inclined plate models, the inclination angles of the inclined plates are different.

3. The surface roughness prediction method of a selective laser melting additively manufactured part according to claim 1, characterized in that: In the same set of inclined plate models, the angle between the upper inclined surface and the horizontal base plate, and the angle between the lower inclined surface and the horizontal base plate are 20-55°.

4. The surface roughness prediction method of a selective laser melting additively manufactured part according to claim 1, characterized in that: In step 3, the inclined workpiece is separated from the substrate by wire cutting.

5. The method for predicting the surface roughness of a selective laser melting additively manufactured part according to claim 1, characterized in that: In step 3, the upper inclined surface is an inclined surface whose angle between the surface normal vector and the positive direction of the forming direction is an acute angle; the lower inclined surface is an inclined surface whose angle between the surface normal vector and the positive direction of the forming direction is an obtuse angle.

6. The method for predicting the surface roughness of a selective laser melting additively manufactured part according to claim 1, characterized in that: In step 3, the roughness of the upper inclined surface and the lower inclined surface is measured by a laser confocal optical microscope, and the magnification of the microscope is 1000 times.

7. The method for predicting the surface roughness of a part manufactured by selective laser melting additive manufacturing according to claim 1, characterized in that: In step 3, for the same plane, the average values ​​of the lateral roughness measured several times and the longitudinal roughness measured several times are calculated as the roughness of the measured inclined surface.

8. The method for predicting the surface roughness of a selective laser melting additively manufactured part according to claim 1, characterized in that: In step 4, the mathematical fitting process is to mathematically fit the upper inclined surface roughness and the lower inclined surface roughness obtained in step 3 for the same group of inclined workpieces by the least squares method to obtain a polynomial, which is the roughness prediction model for the same group of inclined workpieces.

9. The method for predicting the surface roughness of a selective laser melting additively manufactured part according to claim 8, characterized in that: The highest degree of the polynomial is 2.

10. The method for predicting the surface roughness of a part manufactured by selective laser melting additive manufacturing according to claim 8, characterized in that: In step 5, the printing direction and the direction of the scraper spreading powder are determined according to the roughness prediction result of the inclined workpiece to be printed and the roughness requirement of the inclined workpiece to be printed.

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