Additive manufacturing method and device for optimizing and enhancing material properties using region-specificity

Abstract

Provided are an additive manufacturing method and device for optimizing the performance of an enhanced material by utilizing regional specificity, wherein a model for forming a component is divided into at least one first region and a second region with different performance requirements according to a target specific distribution of the component; a first melting process parameter is set for the first region, and a second melting process parameter is set for the second region, wherein consolidation using the first melting process parameter is superior to consolidation using the second melting process parameter in terms of a first characteristic, and consolidation using the second melting process parameter is superior to consolidation using the first melting process parameter in terms of a second characteristic; and according to the set first melting process parameter and second melting process parameter, a melting scan is performed on powder materials laid layer by layer on a building platform to match the first region and the second region to obtain a finally formed component, so as to optimize the specific performance of each region and meet the specific requirements of different regions while improving the overall performance of the component.

Description

Technical Field

[0001] The present disclosure relates to the field of additive manufacturing, and more particularly to an additive manufacturing method and apparatus for optimizing the performance of enhanced materials using region specificity. Background Art

[0002] In the process of Additive Manufacturing (AM), the melting and consolidation of materials directly affect the performance of the final component. Different manufacturing process parameters will lead to different crystal structures and material properties. However, due to the different working conditions and stress conditions of components in actual use, the performance requirements of different parts are also different. Therefore, how to reasonably set and optimize the manufacturing process parameters of different areas according to the specific use and working conditions of the components to meet the performance requirements of different areas has become an important research direction of additive manufacturing technology. However, it is difficult for existing technologies to achieve regional specific optimization in the same component, which limits the application of additive manufacturing technology in the manufacture of high-performance components. Summary of the invention

[0003] The present disclosure proposes an additive manufacturing method and device that utilizes regional specificity to optimize and enhance material performance. Melting process parameters with different performance characteristics are set for different regions according to the target specific distribution of the component, so as to achieve specific performance optimization of each region, thereby improving the overall performance of the component while meeting the specific needs of different regions.

[0004] In a first aspect, the present disclosure provides an additive manufacturing method, the method comprising: dividing a model for forming a component into at least one first region and a second region with different performance requirements according to a target-specific distribution of the component; setting a first melting process parameter for the first region, and setting a second melting process parameter for the second region, wherein consolidation with the first melting process parameter is superior to consolidation with the second melting process parameter in terms of a first characteristic, and consolidation with the second melting process parameter is superior to consolidation with the first melting process parameter in terms of a second characteristic; and performing a melting scan on powder materials laid layer by layer on a building platform according to the set first melting process parameter and second melting process parameter to match the first region and the second region to obtain the finally formed component.

[0005] Preferably, the first characteristic includes at least one of density, strength and toughness, and the second characteristic includes at least one of smoothness, roughness, corrosion resistance and wear resistance.

[0006] Preferably, the first region comprises an inner region of the component, the second region comprises an edge region of the component, and the inner region and the edge region are at least partially arranged relative to a horizontal direction and / or a vertical direction of the component.

[0007] Preferably, the model used to form the component is divided into at least one first area and a second area with different performance requirements according to the target-specific distribution of the component, including: establishing an environmental model that reflects the working state of the component in actual use; defining material properties and boundary conditions of the component and the surrounding environment, wherein the boundary conditions include fixed supports in contact with the component, constraints and contact surface friction coefficients; applying actual use loads related to the purpose of the component, wherein the loads include static loads, dynamic loads and impact loads; performing finite element meshing on the environmental model and calculating the mechanical distribution state of the component under different loads and boundary conditions using finite element analysis to determine the target-specific distribution; and setting the area with a higher demand for the first characteristic than the second area determined according to the target-specific distribution as the first area, and setting the area with a higher demand for the second characteristic than the first area as the second area.

[0008] Preferably, the first melting process parameter has at least a lower laser power and a higher scanning rate than the second melting process parameter, and the second melting process parameter has at least a higher laser power and a lower scanning rate than the first melting process parameter.

[0009] Preferably, the laser power of the first melting process parameters is 100-200 W, and the scanning rate is 1000-3000 mm / s, and the laser power of the second melting process parameters is 200-400 W, and the scanning rate is 500-1000 mm / s.

[0010] Preferably, it also includes performing melting scanning in the first area and the second area with the first melting process parameter and the second melting process parameter changing progressively in adjacent layer sections or adjacent passes of the same layer section of the component, so that the laser power and the scanning rate gradually increase or decrease.

[0011] Preferably, the first region includes a stress concentration area and / or a joint portion of the component, and the second region includes an outer surface and / or a non-stress concentration area of ​​the component.

[0012] Preferably, it also includes repeated melting in the first region and / or the second region, wherein, when the first region is repeatedly melted, the process parameters of the repeated melting have higher laser power and lower scanning rate relative to the first melting process parameters to improve the first characteristics of the first region; when the second region is repeatedly melted, the process parameters of the repeated melting have lower laser power and higher scanning rate relative to the second melting process parameters to improve the second characteristics of the second region.

[0013] Preferably, when the first area is repeatedly melted, the laser power of the process parameters of the repeated melting is 200W-400W, and the scanning rate is 500-1000 mm / s; when the second area is repeatedly melted, the laser power of the process parameters of the repeated melting is 100-200W, and the scanning rate is 2000-5000mm / s.

[0014] Preferably, before repeatedly melting the first region, the method further comprises applying nanoparticles to at least a portion of the first region.

[0015] In a second aspect, the present disclosure provides an apparatus for additive manufacturing, wherein the apparatus is configured to manufacture a component according to the method described in any one of the first aspects.

[0016] In a third aspect, the present disclosure provides a component manufactured according to the method described in any one of the first aspects. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings, which are incorporated herein and form a part of the specification, illustrate one or more embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure and to enable one of ordinary skill in the relevant art to make and use the present disclosure.

[0018] Figure 1 A schematic process diagram of additive manufacturing according to some embodiments of the present disclosure is shown;

[0019] Figure 2 A schematic regional division diagram showing components of some embodiments of the present disclosure is shown;

[0020] Figure 3 A schematic diagram of a guide section in some embodiments of the present disclosure is shown;

[0021] Figure 4 A schematic area division flowchart of components of some embodiments of the present disclosure is shown;

[0022] Figure 5 A schematic flowchart of using a machine learning model to divide component areas in some embodiments of the present disclosure is shown;

[0023] Figure 6 Schematic progressive change diagrams of melting process parameters of some embodiments of the present disclosure are shown, wherein (a) shows the progressive change of melting process parameters in adjacent layer sections of a component, and (b) shows the progressive change of melting process parameters in adjacent passes of a layer section;

[0024] Figure 7 and Figure 8The microstructure comparison diagrams of the titanium alloy (Ti-6Al-4V) samples after being processed by the high-speed repeated melting strategy and the traditional titanium alloy (Ti-6Al-4V) samples of some embodiments of the present disclosure are respectively shown;

[0025] Fig. 9 A schematic process diagram of applying nanoparticles according to some embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0026] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the disclosure will be more comprehensive and complete and the concepts of the example embodiments are fully conveyed to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure.

[0027] The "additive manufacturing" involved in the present disclosure refers to a 3D printing technology (such as selective laser melting (SLM)) that manufactures three-dimensional objects by adding powder materials layer by layer and consolidating the powder materials using an energy beam (such as a laser or electron beam). This technology uses a digital model generated by computer-aided design (CAD) software to precisely control the melting and consolidation process of the powder materials to build complex three-dimensional objects layer by layer, that is, the "components" involved in the present disclosure. In practical applications, components can be functional parts, structural parts, tools or any other physical items, and their design and manufacture can be customized according to the specific needs of their final use. The "powder materials" involved are the raw materials used in additive manufacturing components, including but not limited to metal powders, ceramic powders, polymer powders and composite material powders. The "consolidation" involved refers to the process in which the powder material undergoes a transformation from a discrete particle state to a continuous entity structure under the action of an energy beam. For example, this transformation involves the partial melting of powder particles after absorbing energy to form a liquid molten pool, and then as the energy is withdrawn and the material cools, the liquid molten pool gradually solidifies and finally consolidates into a tightly connected entity structure with a stable form.

[0028] [Overview of the present disclosure]

[0029] Figure 1 The schematic process of additive manufacturing disclosed in the present invention is shown. Figure 1 , the present disclosure generally relates to a component 13 ( Figure 1 Shown is a layer cross section of a component 13 ) performing region division corresponding to target specificity, and performing manufacturing with different process parameters according to the divided regions.

[0030] The division of regions is performed in the digital model (the desired form of the component 13) used to form the component 13. The model is divided into one or more first regions 13A and one or more second regions 13B according to the target specificity of the component 13. The range of the division is flexible and optional. For example, the first region 13A and the second region 13B may cover the entire component 13 or only a part of the component 13 (the undivided region may use conventional process parameters).

[0031] According to the division results, different process parameters are formulated for different regions. For example, the first melting process parameter P1 is set for the first region 13A, and the second melting process parameter P2 is set for the second region 13B. The formulation of the process parameters depends on the difference in performance requirements between the first region 13A and the second region 13B. The first region 13A has higher requirements for the first characteristic, such as density, strength and toughness; while the second region 13B has higher requirements for the second characteristic, such as smoothness, roughness, corrosion resistance and wear resistance. Therefore, the first region 13A consolidated by the first melting process parameter P1 is superior to the second region 13B consolidated by the second melting process parameter P2 in terms of the first characteristic; and the second region 13B consolidated by the second melting process parameter P2 is superior to the first region 13A consolidated by the first melting process parameter P1 in terms of the second characteristic.

[0032] In the energy beam-based additive manufacturing process, the process parameters will change adaptively with the switching of regions. That is, when the powder material 12 (presented as a powder bed on the building platform 13) laid layer by layer on the building platform 11 is melt-scanned, when the scanning path is in the first region 13A, the energy beam performs a melt scan of the corresponding region with the first melt process parameter P1; and when the scanning path is switched to the second region 13B, the energy beam will perform a melt scan of the corresponding region with the second melt process parameter P2. This ensures that the characteristic requirements of each region are met, thereby forming the final component 13.

[0033] [First implementation method of regional division]

[0034] Figure 2 Schematic division of regions of the disclosed component 13 is shown. Figure 2In some embodiments of the present disclosure, the target specificity of the component 13 can be summarized as the distribution difference of the region, and this distribution difference is reflected in the difference between the internal region and the external region of the component 13. Specifically, the internal region of the component 13 can be identified as the first region 13A, and the edge region of the component 13 can be identified as the second region 13B. This division is based on the fact that the internal region and the edge region of the component 13 have different performance requirements. For example, the first region 13A (internal region) generally requires higher density, strength and toughness to ensure that the component 13 has sufficient structural integrity when subjected to internal stress. The second region 13B (edge ​​region) may require higher smoothness, roughness, corrosion resistance and wear resistance to ensure that the component 13 has good surface properties and durability during use.

[0035] In a specific setting, the first region 13A (inner region) and the second region 13B (edge ​​region) can be at least partially set relative to the horizontal direction and / or vertical direction of the component 13. For example, in the Z-axis direction of the component 13, a portion extending downward from the top and / or extending upward from the bottom can be regarded as the second region 13B, while the middle portion is regarded as the first region 13A, so that the component 13 has different characteristics in the longitudinal direction to meet the performance requirements at different positions. For example, in any layer section in the X / Y-axis direction of the component 13, the middle portion can be regarded as the first region 13A, while the edge portion is regarded as the second region 13B, so that the component 13 has different characteristics in the cross section, thereby improving the overall performance.

[0036] In addition, the area ratio of the first area 13A and the second area 13B is not particularly limited. For example, the first area 13A can be infinitely close to the edge area and occupy a relatively large area. Similarly, the area of ​​the second area 13B can also be adjusted accordingly to meet specific performance requirements. The specific division method can be adjusted according to the specific application scenario and the actual use requirements of the component 13 to ensure the best performance in different areas.

[0037] [Variation of the first embodiment of region division]

[0038] As a variation of the first implementation of area division, the difference in area distribution is not only reflected in the difference between the inner area and the edge area of ​​the component 13, but also in the functional requirements of different parts of the component 13. For example, Figure 3A guide section is shown, which is composed of multiple rotating spring structures and fixed sections. The rotating spring structure is used as a bendable section to achieve precise guidance and flexible movement in a narrow channel. In order to ensure that it can withstand various stresses and pressures during use, each small section of the rotating spring structure needs to have sufficient strength and durability. It can be easily determined that in the guide section, the rotating spring structure and the fixed section have different functional requirements. For example, for the rotating spring structure, it is necessary to have a higher strength to withstand the stress when bending in a narrow channel, and it must have sufficient toughness to prevent breakage during repeated bending. At the same time, it is also necessary to have good durability to ensure stable performance during multiple uses. For the fixed section, it is necessary to have a higher stability to ensure that it can maintain a precise position during operation, and at the same time, it is necessary to have a higher rigidity to provide support to prevent deformation during use. According to the different functional requirements of the rotating spring structure and the fixed section, corresponding process parameters can be formulated, for example, the rotating spring structure (first area 13A) is set to the first melting process parameter P1, and the fixed section (second area 13B) is set to the second melting process parameter P2. In the additive manufacturing process, when the melting scanning path is located at the rotating spring structure (first area 13A), the first melting process parameter P1 is used for scanning to ensure the high strength and high toughness of the rotating spring structure; when the melting scanning path is located at the fixed joint (second area 13B), the second melting process parameter P2 is used for scanning to ensure the high rigidity and high wear resistance of the fixed joint. In this way, the optimized manufacturing of different parts of the guide joint can be achieved in the additive manufacturing process, ensuring that the functional requirements of the rotating spring structure and the fixed joint during use are fully met.

[0039] [Second implementation method of regional division]

[0040] Figure 4 20 is a schematic region division process of the component 13 of the present disclosure. In some embodiments of the present disclosure, digital simulation can also be used to determine the target specific distribution by simulating the working state of the component 13 in actual use, for example, by Figure 4 The process 20 described is implemented. The process 20 includes the following steps 21-25.

[0041] 21. Build an environmental model

[0042] The environmental model refers to a model that can reflect the working state of the component 13 in actual use (including the geometry of the component 13 and the geometry of the environment surrounding the component 13). The model needs to take into account the actual working environment of the component 13 to ensure the accuracy of the simulation results. For example, in order to reflect the actual working state of the component 13, the environmental parameters in which it is in use can be collected and determined, including but not limited to temperature, humidity, pressure, and medium environment. If there are other objects (such as brackets, connectors, etc.) in the working environment of the component 13 that interact with it, it is necessary to simultaneously establish the geometric models of these objects to accurately simulate their stress and heat transfer conditions.

[0043] 22. Define material properties and boundary conditions

[0044] Step 22 involves defining the material properties and boundary conditions of the component 13 and its surroundings. The material properties of the component 13 may include, for example, the elastic modulus, density, Poisson's ratio, expansion coefficient, and thermal conductivity of the component 13 material, and the environmental material properties of the component 13 may include, for example, the air thermal conductivity and liquid viscosity of the surrounding environment of the component 13. Taking titanium alloy (Ti-6Al-4V) as an example, an exemplary material property is shown in the following table:

[0045]

[0046] Boundary conditions may include, for example, fixed supports in contact with the component 13, constraints, and contact surface friction coefficients (friction coefficients between the component 13 and other objects), etc. These definitions can effectively simulate the behavior of the component 13 in actual use. For example, the bottom fixed support can be achieved by constraining all degrees of freedom of the bottom node, and the constraints can impose horizontal and / or vertical constraints on the side of the component 13.

[0047] 23. Apply actual load

[0048] The applied load is the actual use load related to the purpose of the component 13. The load can be divided into static load, dynamic load and impact load. Static load refers to the constant load that the component 13 bears under normal working conditions, which can be applied to the top or specific area of ​​the model. Dynamic load includes periodic or randomly changing loads that the component 13 is subjected to during operation, such as mechanical vibration or kinetic energy shock, which can be set as a sine wave or other periodic function. Impact load is a severe load applied in a short period of time, which can simulate high-intensity force in a short period of time. By applying these loads, the stress conditions of the component 13 under various working conditions can be simulated.

[0049] 24. Finite element meshing and analysis

[0050] After the environmental model with material properties and boundary conditions is established and defined and the actual use load is applied, the environmental model is meshed by finite element. Exemplarily, the mesh can be divided by tetrahedral unit type, and the mesh size is set to 1mm or less to ensure the precision of the simulation calculation. Through the meshing process, the component 13 and its working environment are divided into multiple small units, so that the finite element analysis (FEA) can more accurately calculate the mechanical distribution state of the component 13 under different loads and boundary conditions. Finite element analysis can provide mechanical information such as stress, strain and displacement of the component 13 at different positions. For example, stress can be obtained by the formula F=σ*A, where σ is stress, F is the applied load, and A is the force area; strain can be obtained by the formula ΔL=ε*L0, where ε is strain, ΔL is the deformation length, and L0 is the original length.

[0051] 25. Identify specific regions

[0052] According to the results of finite element analysis, the target specific distribution of component 13 is determined. By analyzing the mechanical distribution state of component 13 at different positions, it can be determined which areas have higher requirements for a certain characteristic. For example, for areas requiring higher strength and toughness, they can be set as the first area 13A; for areas requiring higher smoothness and wear resistance, they can be set as the second area 13B. Specifically, by analyzing the stress distribution results, the stress concentration areas in component 13 are determined. These areas usually require higher strength and toughness and can be set as the first area 13A. The stress, strain and displacement on the surface of component 13 are analyzed to determine the areas requiring higher smoothness and wear resistance. These areas can be set as the second area 13B. According to the analysis results, component 13 is divided into different characteristic areas, and corresponding process parameters are set for different areas. The first area 13A adopts the first melting process parameter P1 to achieve higher strength and toughness; the second area 13B adopts the second melting process parameter P2 to achieve higher smoothness and wear resistance. During the additive manufacturing process, the corresponding melting process parameters are switched according to the characteristic requirements of different regions to ensure that the characteristic requirements of each region are met to form the final component 13.

[0053] [Third embodiment of region division]

[0054] As an alternative or addition to the second embodiment of the area division, the areas can be divided according to the stress concentration area and the non-stress concentration area of ​​the component 13. Specifically, the first area 13A can be set as the stress concentration area and / or the joint part of the component 13, and the second area 13B can be set as the outer surface of the component 13 and / or the non-stress concentration area.

[0055] It should be understood that stress concentration areas refer to areas on the component 13 where stress increases significantly due to sudden shape changes, load concentration or other reasons. These areas are prone to cracks or damage during use, so they need to have higher strength and toughness to ensure that they will not break or fail when subjected to high stress. Joint parts refer to areas on the component 13 that need to move flexibly or withstand cyclic loads. For example, the joints of a robotic arm, the connection points of moving parts, etc. These parts will move or deform repeatedly during use, so they need to have good fatigue strength and durability to ensure reliable performance under long-term use and multiple cyclic loads. The outer surface refers to the external visible part of the component 13, which usually requires high surface quality (good finish and low roughness) and wear resistance to meet the requirements of aesthetics and long-term use. Non-stress concentration areas refer to areas on the component 13 where stress is small or stress distribution is uniform. These areas have relatively low requirements for material strength and toughness, but may need to meet other specific performance requirements, such as corrosion resistance or thermal stability.

[0056] According to the different performance requirements of stress concentration areas and non-stress concentration areas, corresponding process parameters can be formulated. For example, for the high strength, high toughness and high fatigue strength requirements of stress concentration areas and / or joints, the first melting process parameter P1 is set to ensure the density and mechanical properties of the material. For the high finish, high wear resistance and specific performance requirements of the outer surface and non-stress concentration areas, the second melting process parameter P2 is set to achieve the required surface quality and specific performance. During the additive manufacturing process, according to the functional requirements of different areas, the corresponding melting process parameters are switched to ensure that the characteristic requirements of each area are met. For example, when the melting scanning path is located in the stress concentration area or the joint area (the first area 13A), the first melting process parameter P1 is used for scanning to ensure the high strength, high toughness and high fatigue strength of these areas. When the melting scanning path is located on the outer surface or the non-stress concentration area (the second area 13B), the second melting process parameter P2 is used for scanning to ensure the high finish, high wear resistance and specific performance of these areas. In this way, optimized manufacturing of different parts of component 13 can be achieved during the additive manufacturing process, ensuring that the functional requirements of stress concentration areas, joints, outer surfaces and non-stress concentration areas during use are fully met, thereby improving the overall performance and service life of component 13.

[0057] [Other implementation methods of regional division]

[0058] In other possible implementations, a machine learning model may be introduced to automatically identify regions with different performance requirements in the component 13, namely, the first region 13A (higher requirements for the first characteristic) and the second region 13B (higher requirements for the second characteristic). This method can improve the accuracy and efficiency of region division and is suitable for complex components.

[0059] Figure 5 FIG. 3 shows a schematic process of using the machine learning model 30 to divide the component 13 area in the present disclosure. Figure 5 The introduction and training process of the machine learning model 30 generally involves steps such as data collection, feature extraction, model training and model optimization. The specific machine learning model 30 can include but is not limited to deep neural network (DNN), support vector machine (SVM), random forest (RF), etc., and the optimal model is selected according to specific needs and data characteristics.

[0060] Specifically, a large amount of historical manufacturing data containing different performance requirements of the component 13, including geometric information, material properties, processing parameters and actual performance test results of the component, is collected for the training device 31 to train the machine learning model 30. The training device 30 is configured to mark the collected data, mark the performance requirements of different regions (such as strength, toughness, finish, etc.) to provide labels for the machine learning model 30. In addition, the training device 30 is also used to extract the features of the component 13, which may include geometric features, material features and processing features. Geometric features include, for example, the size, shape, curvature, cross-sectional changes of the component 13 to reflect the structural characteristics and stress distribution of the component 13. Material features include, for example, the elastic modulus, Poisson's ratio and density of the component 13 to reflect the basic mechanical properties of the material. Processing features include, for example, laser power, scanning rate and layer thickness to reflect the processing conditions of different regions in the manufacturing process. After feature extraction, the training device 30 uses the collected training data and features for model training, so that the machine learning model 30 can identify the performance requirements of different regions in the component 13 by learning the rules in the data. In addition, the training device 31 can also use verification data that is not involved in the training to verify the model, evaluate the recognition accuracy and robustness of the model, and adjust the model parameters and training strategies based on the verification results to further optimize the performance of the machine learning model 30.

[0061] During the application of the machine learning model 30, by inputting the geometric information, material properties and initial processing parameters of the component 13 to be manufactured into the trained machine learning model 30, the machine learning model 30 can automatically identify areas with different performance requirements in the component 13 and divide them into a first area 13A (with a higher demand for the first characteristic) and a second area 13B (with a higher demand for the second characteristic).

[0062] Application example: Collect geometric information, processing parameters and actual performance data of titanium alloy (Ti-6Al-4V) components. For example, under specific processing parameters, a batch of components has a strength of 1000 MPa, a toughness of 30 J / cm², and a smoothness of 0.8 μm. Extract geometric features (such as the size and curvature of the component), material features (such as elastic modulus 113.8 GPa, Poisson's ratio 0.342), and processing features (such as laser power 200W, scanning rate 1500 mm / s). Train a machine learning model and use the model to divide new components into regions. For example, the stress concentration area of ​​the component is identified as the first region 13A, which requires high strength and high toughness; the outer surface is the second region 13B, which requires high smoothness and wear resistance.

[0063] In addition, the machine learning model 30 can also automatically generate process parameters that meet different performance requirements based on the identified areas. For example, if the first area 13A requires high strength and high toughness, it is recommended to use a higher laser power and a moderate scanning rate; if the second area 13B requires high finish and high wear resistance, it is recommended to use a lower laser power and a higher scanning rate. In the actual additive manufacturing process, the additive manufacturing system can also dynamically adjust the melting process parameters according to the suggestions of the machine learning model 30 to ensure that the performance requirements of different areas are fully met. For example, in the actual manufacturing process, the melting process parameters are dynamically adjusted: when the scanning path is located in the first area 13A, a laser power of 250W and a scanning rate of 1500 mm / s are used; when the scanning path is located in the second area 13B, a laser power of 150W and a scanning rate of 2000 mm / s are used.

[0064] [Determination and application of melting process parameters]

[0065] In some embodiments of the present disclosure, different melting process parameters are set according to different regional requirements to achieve performance optimization of different parts of the component 13. Specifically, the setting of the first melting process parameter P1 and the second melting process parameter P2 can be achieved by adjusting the laser power and the scanning rate according to the performance requirements of different regions. For example, the first melting process parameter is set to have at least a lower laser power and a higher scanning rate than the second melting process parameter, and the second melting process parameter is set to have at least a higher laser power and a lower scanning rate than the first melting process parameter.

[0066] Since the first melting process parameter P1 is mainly used in the first region 13A, this region has a higher demand for the first characteristic (such as high strength and high toughness). In order to achieve these characteristics, the optional first melting process parameter is set as follows: laser power is about 100-200W, and the scanning rate is about 1000-3000mm / s. It should be understood that lower laser power is conducive to reducing excessive melting and thermal stress, maintaining the density and toughness of the material, and higher scanning rate can reduce heat input time, reduce heat accumulation, and avoid overheating of the material, thereby ensuring the strength and toughness of the material. Through this setting, the first melting process parameter P1 can make the first region 13A superior in mechanical properties and is suitable for component parts requiring high strength and high toughness. Since the second melting process parameter P2 is mainly used in the second region 13B, this region has a higher demand for the second characteristic (such as high finish and high wear resistance). In order to achieve these characteristics, the optional second melting process parameter is set as follows: laser power is about 200-400W, and scanning rate is about 500-1000mm / s. It should be understood that a higher laser power can ensure that the material is fully melted, improve the surface finish and density, and thus enhance the wear resistance, and a lower scanning rate is conducive to increasing the interaction time between the laser and the material, ensuring the surface flatness and finish of the material. Through this setting, the second melting process parameter P1 can make the second region 13B superior in surface characteristics, and is suitable for component parts that require high finish and high wear resistance.

[0067] In order to better understand the setting of melting process parameters, the following is explained by a specific example: It should be understood that the laser power and scanning rate have a direct impact on the heat input during the melting process, which can be simply expressed as P=H*V, where P is the laser power and V is the scanning rate. By adjusting P and V, the heat input can be controlled, thereby affecting the melting state and cooling rate of the powder material.

[0068] Non-limiting, for example, assume that the first melting process parameter P1 is a laser power of 150W and a scanning rate of 2500mm / s. Under this setting, the heat input is small, the material can be cooled quickly, and a dense structure is formed, which is suitable for the requirements of high strength and high toughness. Assume that the second melting process parameter P2 is a laser power of 300W and a scanning rate of 800mm / s. Under this setting, the heat input is large, the material is fully melted, and the cooling is slow, forming a flat and smooth surface, which is suitable for the requirements of high finish and high wear resistance. Through different melting process parameter settings, the additive manufacturing process can be dynamically adjusted according to regional requirements to ensure that the performance requirements of different regions of the component 13 are met. For example, when the energy beam scanning path is located in the first region 13A, a laser power of 150W and a scanning rate of 2500mm / s are used for melting scanning to ensure the density and toughness of the material in the region. When the energy beam scanning path is located in the second region 13B, a laser power of 300W and a scanning rate of 800mm / s are used for melting scanning to ensure the finish and wear resistance of the material in the region.

[0069] By setting different melting process parameters for different areas, the additive manufacturing method disclosed in the present invention can achieve local optimization while ensuring the overall performance of component 13, thereby meeting the diverse performance requirements of complex components. This not only improves manufacturing efficiency, but also significantly improves the performance of component 13, making it suitable for high-demand industrial applications.

[0070] In some embodiments, the melting process parameters are not limited to laser power and scanning rate, but may also include spot diameter, overlap rate, scanning path, layer thickness, etc. By adjusting these parameters, the performance requirements of different regions can be further optimized to ensure the forming quality of components during the additive manufacturing process.

[0071] The spot diameter affects the energy distribution of the laser beam on the powder bed and the size of the molten pool. A smaller spot diameter can achieve high-resolution and detailed processing, and a larger spot diameter can improve the melting efficiency. Appropriate spot diameters can be selected for different areas. For example, the first area 13A uses a smaller spot diameter to achieve high-precision processing, and the second area 13B uses a larger spot diameter to improve surface flatness. The overlap rate refers to the degree of overlap between laser scanning paths. A higher overlap rate can improve the uniformity and density of the molten pool, but may reduce efficiency. By adjusting the overlap rate, performance optimization can be achieved in different areas. For example, the first area 13A uses a higher overlap rate to enhance the density of the material, and the second area 13B uses a lower overlap rate to improve processing efficiency. The scanning path affects the thermal gradient and stress distribution. The optimized scanning path can reduce thermal deformation and residual stress. Designing different scanning paths for different areas can significantly improve the performance of the component. For example, the first area 13A uses a cross scanning path to evenly distribute heat, and the second area 13B uses a parallel scanning path to ensure surface quality.

[0072] [Progressive changes in melt process parameters]

[0073] Figure 6 The schematic progressive changes of the melting process parameters of the present disclosure are shown, wherein (a) shows the progressive changes of the melting process parameters in adjacent layer sections of the component 13, and (b) shows the progressive changes of the melting process parameters in adjacent passes of the layer sections. As a variation of the determination and application of the melting process parameters, in some embodiments of the present disclosure, in order to further optimize the performance of the component 13, melting scans can also be performed in the first area 13A and the second area 13B in adjacent layer sections of the component 13 or adjacent passes of the same layer section with progressively changing first melting process parameters P1 and second melting process parameters P2, so that the laser power and the scanning rate are gradually increased or decreased. In this way, the laser power and the scanning rate can be gradually adjusted without significantly changing the overall process, so that different parts of the component 13 can achieve optimal performance.

[0074] Reference Figure 6 (a), between adjacent layer sections of the component 13, the melting process parameters can be gradually changed layer by layer. Exemplarily, in the first region 13A, the laser power can be gradually increased from a lower value. For example, the laser power of the first layer is set to 150W, the second layer is set to 160W, the third layer is set to 170W, and so on. In the second region 13B, the laser power can be gradually reduced from a higher value. For example, the laser power of the first layer is set to 350W, the second layer is set to 340W, the third layer is set to 330W, and so on. In the first region 13A, the scanning rate can be gradually reduced from a higher value. For example, the scanning rate of the first layer is set to 2500mm / s, the second layer is set to 2400mm / s, the third layer is set to 2300mm / s, and so on. In the second region 13B, the scanning rate can be gradually increased from a lower value. For example, the scanning rate of the first layer is set to 800mm / s, the second layer is set to 850mm / s, the third layer is set to 900mm / s, and so on. The advantage of this gradual change is that the melting conditions can be gradually adjusted to make the material transition between layers smoother, reduce stress concentration and deformation risks, and ensure the overall performance of the component.

[0075] Reference Figure 6(b), between adjacent passes of the same layer cross section, the melting process parameters can also be changed gradually. Exemplarily, in the first region 13A, the laser power can be gradually increased between adjacent passes. For example, the laser power of the first pass in the first region is set to 150W, the second pass is set to 155W, the third pass is set to 160W, and so on. In the second region 13B, the laser power can be gradually reduced between adjacent passes. For example, the laser power of the first pass in the second region is set to 350W, the second pass is set to 345W, the third pass is set to 340W, and so on. In the first region 13A, the scanning rate can be gradually reduced between adjacent passes. For example, the scanning rate of the first pass in the first region is set to 2500mm / s, the second pass is set to 2450mm / s, the third pass is set to 2400mm / s, and so on. In the second region 13B, the scanning rate can be gradually increased between adjacent passes. For example, the scanning rate of the first pass in the second area is set to 800 mm / s, the second pass to 850 mm / s, the third pass to 900 mm / s, etc. By making gradual changes between adjacent passes in the same layer section, more detailed process adjustments can be achieved to further optimize the characteristics of different areas of the component.

[0076] It should be understood that the progressive changes, including the progressive changes of adjacent layer cross sections and the progressive changes of adjacent passes of layer cross sections, are performed separately in the first region 13A and the second region 13B. That is, in the first region 13A, the progressive changes of the laser power and the scanning rate are adjusted only according to the characteristic requirements of the first region and will not be affected by the second region 13B. Similarly, in the second region 13B, the progressive changes of the laser power and the scanning rate are adjusted only according to the characteristic requirements of the second region 13B and will not be affected by the first region 13A. The melting process parameters of each region are independently set according to its specific requirements, ensuring that the process parameters of each region are optimized to meet its specific performance requirements.

[0077] [Multi-energy beam melting]

[0078] Taking laser as an example, in some embodiments of the present disclosure, multiple lasers can be set to perform melting scans in different areas, and in particular, at least two laser beams can be set, respectively for melting scans of the first area 13A and the second area 13B. According to specific needs, the number of laser beams can be further increased to accommodate more regional divisions and complex geometric structures. The configuration of each laser beam can be optimized according to the performance requirements of its target area. For example, the laser beam of the first area 13A can be set with a lower laser power and a higher scanning rate to improve the strength and toughness of the area; the laser beam of the second area 13B can be set with a higher laser power and a lower scanning rate to improve the finish and wear resistance of the area. Multiple laser beams can work synchronously, each responsible for the melting scan of its target area, so as to significantly improve manufacturing efficiency and reduce the manufacturing time of the entire component. In addition, the melting process parameters (such as laser power, scanning rate, scanning path, etc.) of each laser beam can be independently controlled to ensure that the specific needs of each area are met. In some cases, an alternating scanning method can also be adopted, that is, two laser beams are alternately melted and scanned to avoid heat accumulation and stress concentration.

[0079] [High-speed repeated melting]

[0080] In some embodiments of the present disclosure, the first region 13A and / or the second region 13B of the component 13 are respectively repeatedly melted, wherein when the first region 13A is repeatedly melted, the process parameters of the repeated melting have a higher laser power and a higher scanning rate relative to the first melting process parameter P1, so as to improve the first characteristic of the first region 13A; when the second region 13B is repeatedly melted, the process parameters of the repeated melting have a lower laser power and a higher scanning rate relative to the second melting process parameter P2, so as to improve the second characteristic of the second region 13B. When the repeated melting is repeated, the surface that has been melted and solidified is melted and scanned again in the same layer or adjacent layers, so as to achieve fine control of the microstructure of the material, thereby improving the comprehensive mechanical properties of the component 13. Specifically, a higher laser power and a scanning rate are used for the first region 13A, and the defects that may be generated during the initial melting are reduced through a rapid secondary melting process, and the grains are refined, thereby improving the mechanical properties of the material. A lower laser power and a higher scanning rate are used for the second region 13B, and the surface is refined and smoothed through the secondary melting process, reducing the surface roughness and improving the wear resistance.

[0081] For example, when the first region 13A is repeatedly melted, the laser power of the repeated melting process parameters is 200W-400W, and the scanning rate is 3000-7000mm / s; when the second region 13B is repeatedly melted, the laser power of the repeated melting process parameters is 100-200W, and the scanning rate is 2000-5000mm / s.

[0082] In some embodiments, the temperature field analysis and process parameter optimization of the molten pool during the primary laser melting and high-speed secondary melting processes can be realized by combining multi-physics field simulation and genetic algorithm optimization, thereby determining the process parameters for repeated melting. The specific implementation process is described in detail below using titanium alloy (Ti-6Al-4V) as an example.

[0083] The multi-physics simulation involves two stages: the primary melting process simulation and the high-speed secondary melting process simulation. The primary melting process simulation mainly involves using the multi-physics simulation software (COMSOL) to construct a three-dimensional model of a titanium alloy (Ti-6Al-4V) component. Exemplary construction parameters are shown in the following table:

[0084]

[0085] The ambient temperature in the table above refers to the temperature of the component and the environment before laser melting begins. During the scanning process, the laser beam will rapidly increase the temperature of the irradiated area, exceeding the melting point of the metal powder. The temperature field will diffuse outward from the center of the laser beam to form a temperature gradient. The heat conduction equation (1.1) can be used to simulate the temperature field change, and the Gaussian distribution model (1.2) can be used to simulate the energy distribution of the laser heat source. , ,in, is the density, is the specific heat capacity, is the temperature, is the thermal conductivity, is the heat source term; is the laser power, is the radial distance, is the spot radius. By running the simulation of the initial melting process, the temperature field distribution cloud map of the molten pool is obtained, the melting isotherm surface is extracted, and the temperature gradient G and solidification rate R of the solid-liquid interface are calculated.

[0086] Among them, the simulation of the high-speed secondary melting process mainly involves running the simulation of the primary and secondary melting processes through multi-physics field simulation software to obtain the temperature field distribution cloud map of the molten pool. The temperature field distribution cloud map shows the temperature changes of titanium alloy components at different positions, especially the high-temperature areas formed during the laser scanning process. Determine the melting isotherm (the surface with an internal temperature equal to the melting point) and calculate the temperature gradient G and solidification rate R of the solid-liquid interface. At the solid-liquid interface, the temperature gradient G is defined as the rate of change of temperature with distance, which can be calculated through the temperature field distribution data (2.1). The solidification rate R is defined as the movement rate of the solid-liquid interface in time, which can be calculated through the change of the temperature field with time (2.2): , ,in, is the temperature, For distance, is the position of the solid-liquid interface, For time.

[0087] According to the CET (columnar to equiaxed crystal transformation) theory, the solidification structure map of titanium alloy (Ti-6Al-4V) is drawn, which shows the microstructure types corresponding to different G and R parameters. The extracted solidification parameters G and R are matched to the structure map to determine whether the solidification parameters are in the equiaxed crystal region. If so, it means that the parameters of the secondary melting process can optimize the microstructure of the component to meet the performance requirements.

[0088] Among them, the optimization of genetic algorithm mainly involves randomly generating a set of process parameters as the initial population, and each individual represents a possible combination of process parameters. Multi-physics field simulation is performed on each individual (process parameter combination) to calculate its corresponding temperature gradient G and solidification rate R. The fitness of each individual is evaluated using the objective function. The objective function can be defined as: ,in, and is the target parameter of the equiaxed crystal region. According to the fitness value, excellent individuals are selected as parents (individuals with high fitness have a higher probability of being selected) and the selected parents are crossovered to generate new individuals (offspring). The crossover operation can generate new individuals by exchanging some parameters of the parents. The new individuals are mutated to randomly change some parameters of the individuals with a certain probability to increase the diversity of the population. Repeat the fitness evaluation, selection, crossover and mutation steps to iteratively generate new populations and gradually improve the fitness of the population. When the fitness of the population reaches the preset threshold or the number of iterations reaches the preset upper limit, the iteration stops.

[0089] Through Figure 7 From the observation and comparison of the microstructure diagrams, it can be seen that the repeated melting strategy disclosed in the present invention effectively improves the microstructure in the traditional titanium alloy (Ti-6Al-4V) specimen. Specifically, the repeated melting strategy breaks the traditional distribution pattern of coarse epitaxial columnar crystals and fine equiaxed crystals at the molten pool boundary. After adopting this strategy, the grain size of the titanium alloy specimen is significantly reduced, the proportion of equiaxed crystals is greatly increased, and the crystal texture is significantly weakened. The fine equiaxed crystals in a layer at the molten pool boundary gradually expand into the entire grain, and the intracrystalline cellular substructure changes from an elongated shape to an approximately equiaxed shape, and its average equivalent diameter is significantly reduced.

[0090] Through Figure 8From the observation and comparison of the microstructure diagrams, it can be found that the titanium alloy (Ti-6Al-4V) specimens treated by the repeated melting strategy disclosed in this disclosure exhibit significant synergistic effects of strength and plasticity, which are specifically manifested in the following aspects: 1) Increased proportion of equiaxed crystals: The increased proportion of equiaxed crystals significantly weakens the stress concentration phenomenon at the boundary of the molten pool, making the geometric discontinuous dislocations (GNDs) more dispersed and uniform. 2) Refinement and equiaxation of the cellular substructure: The refined and equiaxed cellular substructure has a significant improvement in back stress and work hardening, further improving the mechanical properties of the material. 3) Increased density of grain boundaries / subgrain boundaries: The increase in the density of grain boundaries and subgrain boundaries allows the effective stress to continue to increase throughout the tensile stage, thereby significantly improving the elongation and tensile strength of the material.

[0091] In general, the present disclosure can efficiently analyze and optimize the molten pool temperature field and its related process parameters during the primary laser melting and high-speed secondary melting process by combining the optimization method of multi-physics field simulation and genetic algorithm. Specifically, COMSOL multi-physics field simulation software is used to simulate the primary melting and secondary melting, extract key parameters such as temperature field distribution, temperature gradient G and solidification rate R, and draw the solidification structure map based on CET theory to determine whether the solidification parameters are within the equiaxed crystal region. Subsequently, the genetic algorithm is used to optimize the parameters, iteratively generate new process parameter combinations, and continuously improve the fitness until the preset threshold or the upper limit of the number of iterations is reached. Ultimately, the optimized process parameters can significantly improve the microstructure and comprehensive mechanical properties of the component, meet the performance requirements of different regions, and thus achieve the manufacture of high-quality titanium alloy (Ti-6Al-4V) components.

[0092] [Application of Nanoparticles]

[0093] Fig. 9 A schematic process of applying the nanoparticles of the present disclosure is shown. Fig. 9 In some embodiments of the present disclosure, nanoparticles, such as ceramic nanoparticles and / or oxide nanoparticles, may be applied to at least a portion of the first region 13A (such as the stress concentration region and / or the joint) before the first region 13A is repeatedly melted, so as to enhance the performance of the first region 13A in terms of the first characteristic. Ceramic nanoparticles, for example, aluminum oxide (Al2O3) or silicon nitride (Si3N4) are selected, which have high hardness and high wear resistance. Oxide nanoparticles, for example, titanium oxide (TiO2) or zirconium oxide (ZrO2) are selected, which have high melting points and good chemical stability.

[0094] In the specific application process, the nanoparticles can be uniformly dispersed in a solution to prepare a nanoparticle dispersion, and the nanoparticle dispersion can be applied to the surface of the first region 13A using a spraying or coating technique. For example, spray drying, dip coating, or spin coating can be used to ensure that the nanoparticles are uniformly covered in the target area. After spraying or coating the nanoparticles, the first region 13A is dried and preliminarily sintered to ensure good bonding between the nanoparticles and the matrix material.

[0095] During the repeated melting process, the nanoparticles applied to the surface of the first region 13A will be integrated into the matrix material to form a uniform nano-enhanced phase. The addition of nanoparticles can significantly improve the performance of the first region 13A. For example, the addition of ceramic nanoparticles can improve the hardness and wear resistance of the material, while the addition of oxide nanoparticles can improve the high temperature resistance and oxidation resistance of the material. After applying the nanoparticles, the microstructure of the first region 13A will also change. The nanoparticles are distributed as a second phase in the matrix material, which can effectively refine the grains, inhibit grain boundary movement, and improve the comprehensive mechanical properties of the material. Based on the theory of columnar to equiaxed crystal transformation (CET), the addition of nanoparticles can promote grain refinement, so that the first region 13A exhibits a more excellent equiaxed crystal structure after repeated melting, thereby improving its strength and toughness.

[0096] [Performance gradient]

[0097] In additive manufacturing, in order to meet the performance requirements of different regions of the component 13 (such as the first region 13A and the second region 13B), a performance gradient can be formed by designing different material compositions and microstructures. For example, the surface layer has high hardness for wear resistance, and the interior has high toughness for impact resistance.

[0098] Performance gradients can be achieved through material composition design, microstructure design, multiple powder mixing components and progressive melting process parameters alone or in combination: 1) By selecting and mixing different types of powder materials, performance gradients can be formed in different areas of the component 13. For example, high-hardness ceramic powders (such as aluminum oxide, silicon carbide, etc.) are selected and mixed in the metal matrix material to enhance the wear resistance and hardness of the surface. Metal powders with high toughness and impact resistance (such as titanium alloys, nickel-based alloys, etc.) are selected to improve the overall toughness and impact resistance of the component. 2) By controlling the cooling rate and molten pool morphology of the component 13 during the manufacturing process, different microstructures can be formed to achieve performance gradients. For example, a higher cooling rate is used to form a fine equiaxed grain structure, which increases the hardness and wear resistance of the material; a slower cooling rate is used to form a larger columnar grain structure, which enhances the toughness and impact resistance of the material. 3) By adjusting the powder ratio layer by layer, gradient changes in composition and performance can be achieved in different areas of the component 13. For example, during the manufacturing process, the composition of each layer of powder can be adjusted according to design requirements to gradually change the performance of the component 13. For example, gradually increase the ceramic powder content of the surface layer and reduce the metal powder content inside. Use different powder compositions in different areas of the component 13 to optimize the overall performance. For example, use high-hardness ceramic powder in the edge area of ​​the component 13, and use high-toughness metal powder in the center area of ​​the component 13. 4) Combining the progressive change of the melting process parameters disclosed above with the above method can further optimize the performance gradient. For example, different laser powers and scanning rates are used in different areas to achieve different molten pool temperatures and cooling rates, thereby forming different microstructures and properties. Repeated melting is performed in key areas, and the grain structure is further refined and the performance is improved by adjusting the process parameters of repeated melting (such as laser power and scanning rate).

[0099] [Additive manufacturing equipment]

[0100] Some embodiments of the present disclosure also provide an additive manufacturing device, wherein the device is configured to manufacture a component according to any of the additive manufacturing methods / processes described above.

[0101] For example, the device can be composed of a laser melting system, a powder supply system, a temperature monitoring system, a multi-physics simulation system, and a control system. Specifically, the laser melting system is used to perform the initial laser melting and high-speed secondary melting processes, and can achieve progressive melting and repeated melting according to the performance requirements of different regions. The powder supply system is used to supply a variety of powder materials to ensure that powders of different components can be mixed according to design requirements during the manufacturing process to achieve a gradient change in material composition. The temperature monitoring system is used to monitor the temperature distribution of the component during the manufacturing process in real time, and to adjust the laser power and scanning rate through feedback to ensure the stability and uniformity of the molten pool temperature field. The multi-physics simulation system integrates multi-physics simulation software for simulating and analyzing the molten pool temperature field during the initial melting and secondary melting processes, which can extract the temperature gradient G and solidification rate R of the solid-liquid interface, draw solidification structure maps, and optimize process parameters. The control system includes a computer and software, which can automatically control the entire additive manufacturing process according to the input design parameters and process requirements. In addition, the control system integrates a genetic algorithm to optimize the melting process parameters to ensure that the manufactured components have the best microstructure and mechanical properties.

[0102] [Additive manufacturing components]

[0103] In some embodiments of the present disclosure, an additive manufacturing component is also involved. The component is manufactured according to the additive manufacturing method / process described in any of the above items. In some aspects, the component has the following characteristics: 1) The component has different material compositions and microstructures in different regions to meet the specific performance requirements of each region. For example, the surface of the component has high hardness and wear resistance, and the interior has high toughness and impact resistance. 2) By controlling the melting process parameters and repeated melting strategy, the grain size of the component is significantly reduced, the proportion of equiaxed crystals is greatly increased, and the crystal texture is weakened. The intracrystalline cellular substructure changes from an elongated shape to an approximately equiaxed shape, and the average equivalent diameter is significantly reduced, thereby improving the comprehensive mechanical properties of the component. 3) The component after repeated melting treatment shows a significant synergistic effect of strength and plasticity. The increase in the proportion of equiaxed crystals weakens the stress concentration at the boundary of the molten pool, making the dislocation density more dispersed and uniform; the refined and equiaxed cellular substructure has a significant improvement in back stress and work hardening; the increase in the density of grain boundaries and subgrain boundaries causes the effective stress to continue to increase throughout the stretching process, thereby significantly improving the elongation and tensile strength. 4) Applying nanoparticles to key areas of the component (such as the stress concentration area and joints of the first area 13A) to further enhance the characteristics of the area and improve the overall performance.

[0104] It should be understood that the control process of the above method / process in the present application can be implemented in whole or in part through software, hardware, firmware or any other combination.

[0105] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing what is disclosed herein. The present disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary technical means in the art that are not disclosed in the present disclosure. The specification and embodiments are to be considered merely as exemplary, and the present disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes may be made without departing from the scope thereof.

Claims

1. An additive manufacturing method, characterized in that: The method comprises: Dividing a model used to form the component into at least one first region and a second region with different performance requirements according to a target-specific distribution of the component, wherein the first region includes a stress concentration region and / or a joint portion of the component, and the second region includes an outer surface and / or a non-stress concentration region of the component; Setting a first melting process parameter for the first region and setting a second melting process parameter for the second region, wherein consolidation with the first melting process parameter is superior to consolidation with the second melting process parameter in terms of a first characteristic, and consolidation with the second melting process parameter is superior to consolidation with the first melting process parameter in terms of a second characteristic; and According to the set first melting process parameters and second melting process parameters, the powder material laid layer by layer on the building platform is subjected to melting scanning matching the first area and the second area to obtain the finally formed component; The method further comprises performing repeated melting in the first region and / or the second region, wherein: When the first region is repeatedly melted, the process parameters of the repeated melting have a higher laser power and a lower scanning rate relative to the first melting process parameters to improve the first characteristics of the first region; when the second region is repeatedly melted, the process parameters of the repeated melting have a lower laser power and a higher scanning rate relative to the second melting process parameters to improve the second characteristics of the second region.

2. The method according to claim 1, characterized in that The first characteristic includes at least one of density, strength and toughness, and the second characteristic includes at least one of smoothness, roughness, corrosion resistance and wear resistance.

3. The method according to claim 1, characterized in that The first region includes an inner region of the component, the second region includes an edge region of the component, and the inner region and the edge region are at least partially arranged relative to a horizontal direction and / or a vertical direction of the component.

4. The method according to claim 1, characterized in that The step of dividing a model for forming the component into at least one first region and a second region having different performance requirements according to the target-specific distribution of the component comprises: Establishing an environmental model reflecting the working state of the component in actual use; defining material properties and boundary conditions of the component and the surrounding environment, wherein the boundary conditions include fixed supports in contact with the component, constraint conditions, and contact surface friction coefficient; Applying actual use loads related to the purpose of the component, wherein the loads include static loads, dynamic loads and impact loads; Performing finite element meshing on the environmental model and calculating the mechanical distribution state of the component under different loads and boundary conditions using finite element analysis to determine the target-specific distribution; and A region where the demand for the first characteristic is higher than that for the second characteristic determined according to the target-specific distribution is set as a first region, and a region where the demand for the second characteristic is higher than that for the first region is set as a second region.

5. The method according to claim 1, characterized in that The first melting process parameters at least have a lower laser power and a higher scanning rate relative to the second melting process parameters, and the second melting process parameters at least have a higher laser power and a lower scanning rate relative to the first melting process parameters.

6. The method according to claim 5, characterized in that The laser power of the first melting process parameters is 100-200 W, and the scanning rate is 1000-3000 mm / s. The laser power of the second melting process parameters is 200-400 W, and the scanning rate is 500-1000 mm / s.

7. The method according to claim 5, characterized in that It also includes performing melting scanning in the first area and the second area with the first melting process parameter and the second melting process parameter changing progressively in adjacent layer sections or adjacent passes of the same layer section of the component, so that the laser power and the scanning rate gradually increase or decrease.

8. The method according to claim 1, characterized in that When the first region is repeatedly melted, the laser power of the repeated melting process parameters is 200W-400W, and the scanning rate is 500-1000 mm / s; when the second region is repeatedly melted, the laser power of the repeated melting process parameters is 100-200W, and the scanning rate is 2000-5000mm / s.

9. The method according to claim 1, characterized in that: The method further includes applying nanoparticles to at least a portion of the first region before repeatedly melting the first region.

10. A device for additive manufacturing, characterized in that: The apparatus is configured to manufacture a component according to the method according to any one of claims 1-9.

11. A component manufactured according to the method of any one of claims 1 to 9.

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