Integrated digital thread for additive manufacturing design optimization of lightweight structures

Abstract

The present disclosure provides an "Integrated Digital Thread for Additive Manufacturing Design Optimization of Lightweight Structures". A component formed by an additive manufacturing process is provided, the component consisting of three (3) regions: a void region without material; a solid material region; and a non-uniform lattice cell region. The regions are spatially distributed throughout the component according to load conditions, such that the solid material is distributed in the region of a first load path and the lattice cells are distributed in the region of a second load path, the second load path being lower in magnitude than the first load path. The lattice cells are customized according to the additive manufacturing process constraints and the machine resolution.

Description

Technical Field

[0001] The present disclosure relates to additive manufacturing and, more particularly, to a method of designing a part to be formed by an additive manufacturing process. Background Art

[0002] The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.

[0003] Additive manufacturing (AM) or 3D printing has been used to build complex objects with a wide variety of materials and functionalities. AM offers great opportunities for creative structural design with complex geometric features. However, such structures cannot be obtained by traditional design methods such as parametric structural optimization, because of their limited ability to design 3D structures with irregular multi-scale geometric features.

[0004] To address this problem, topology optimization (TO) has been used. Topology optimization (TO) is a mathematical method for optimizing the layout of materials within a given design space for a given set of loads, boundary conditions, and constraints, with the goal of maximizing the performance of the system. TO can contribute to weight reduction by distributing materials to optimal locations.

[0005] Existing TO tools for AM design encounter some problems. First, traditional TO methods (e.g., gradient-based methods) always produce "gray" elements in the final design. Ideally, there should be only two types of elements in the final design: "white" elements (0) representing voids and "black" elements (1) representing solid materials. However, existing software tools generate "gray" elements with values ​​between 0 and 1. In engineering practice, designers always manually set thresholds to classify gray elements into 0 or 1. This special binarization step deviates the results from the global optimization.

[0006] Second, while existing software tools provide the ability to replace "grey" elements with lattice cells, there are no tools for determining the appropriate lattice properties based on the manufacturing capabilities of the AM equipment and methods.

[0007] Third, TO tools cannot be used to create geometric features (e.g., exit holes) required by AM constraints.

[0008] Fourth, no method is known for integrating CAD (computer-aided design), CAE (computer-aided engineering), multi-scale TO and AM. Existing software tools can only focus on one or two aspects of the method.

[0009] Problems associated with the topology of components manufactured using various AM techniques are addressed by the present disclosure. Summary of the invention

[0010] In one form, there is provided a component formed by an additive manufacturing process, the component consisting of three (3) regions: a void region devoid of material; a region of solid material; and a region of non-uniform lattice cells. The regions are spatially distributed throughout the component according to loading conditions such that the solid material is distributed in the region of a first load path and the lattice cells are distributed in the region of a second load path, the second load path being lower in magnitude than the second load path.

[0011] In other features, the lattice unit includes a 6-bar tetrahedral crystal unit, a 16-bar hexahedral element, and a 24-bar hexahedral element. The type and size of the lattice unit varies with the additive manufacturing process. The diameter of each lattice bar of the lattice unit is not equal, and the diameter of each lattice bar of the lattice varies with at least one resolution unit of the additive manufacturing process and the component performance requirements. The material of the component can be selected from the group consisting of metals, ceramics, polymers, composite materials, and plastics.

[0012] In another form, a method of designing a component formed by an additive manufacturing process is provided, the method comprising generating a 3D mesh topology. The 3D mesh topology consists of three (3) regions: void regions devoid of material; regions of solid material; and regions of non-uniform lattice cells. The regions are spatially distributed throughout the component according to loading conditions such that the solid material is distributed in the region of a first load path (also referred to as a "primary" load path) and the lattice cells are distributed in the region of a second load path that is lower in magnitude than the first load path.

[0013] In other features, the diameter of each lattice bar of the lattice unit is optimized based on the load condition so that the diameters are not equal. The diameter of each lattice bar of the lattice is adjusted according to at least one of the resolution unit and component performance requirements of the additive manufacturing process. The method also includes forming a statistical analysis model to generate a statistical distribution of lattice bar diameters and classifying the lattice bars of each lattice into clusters, wherein all lattice cells in the same cluster are assigned an average diameter of the cluster. The average diameter of the cluster is adjusted according to at least one of the resolution unit and component performance requirements of the additive manufacturing process. The method also includes a verification step for verifying that the 3D mesh topology meets the design requirements, and a step for smoothing, flattening and fixing the 3D mesh topology to meet A surface requirements. The method also includes generating additional structural elements, such as geometric features, according to the additive manufacturing process. The geometric features include exit slots for unsintered powder for selective laser sintering (SLS) or uncured resin for stereolithography (SLA) process.

[0014] In yet another form, there is provided a method of manufacturing a component using an additive manufacturing process, the method comprising: manufacturing regions of solid material; manufacturing regions of non-uniform lattice cells; and leaving void regions without material. The regions are spatially distributed throughout the component according to load conditions, such that the solid material is distributed in the region of a first load path (also referred to as a "primary" load path) and the lattice cells are distributed in the region of a second load path, the second load path being lower in magnitude than the first load path.

[0015] In other features, the diameter of each lattice bar of the non-uniform lattice unit is adjusted according to at least one of the resolution unit of the additive manufacturing process and the performance requirements of the component, and the component can be manufactured by different additive manufacturing processes, such as selective laser sintering (SLD), stereolithography (SLA), and fused deposition modeling (FDM).

[0016] Further areas of applicability will become apparent from the description provided herein.It should be understood that the description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present disclosure will be more fully understood from the detailed description and accompanying drawings, in which:

[0018] Figure 1 a flow chart depicting a method of designing a part to be formed by an additive manufacturing process in accordance with the teachings of the present disclosure;

[0019] Figure 2 depicting a separate bar graph showing thresholds for classifying elements into voids, lattice cells, and solid material;

[0020] FIG. 3A to FIG. 3C Depicts the three types of lattice cells used for topology optimization, where Figure 3A is a 6-bar tetrahedral lattice unit. Figure 3B is a 16-bar hexahedral lattice unit, and Figure 3C It is a 24-bar hexahedral lattice unit;

[0021] Figure 4 is a bar graph showing the statistical distribution of grid bar diameters;

[0022] Figure 5 Depicts the design image after lattice size optimization;

[0023] Fig. 6A Depicts the 3D design after topology optimization and lattice size optimization;

[0024] Figure 6B yes Fig. 6A an enlarged view of a portion A of;

[0025] Fig. 7A depicting another 3D design image after topology optimization and lattice size optimization; and

[0026] Figure 7B Depiction Fig. 7A Lattice cells in 3D designs.

[0027] Corresponding reference numerals indicate corresponding parts throughout the several views of the drawings. DETAILED DESCRIPTION

[0028] The following description is merely exemplary in nature and is not intended to limit the present disclosure, application, or uses.

[0029] The present disclosure provides a method for designing a part to be formed by an additive manufacturing (AM) process. The method of the present disclosure provides an integrated digital thread for the design of a successful implementation of an AM process. The digital thread used herein refers to a communication framework that allows for a connected data flow and an integrated view of data throughout the design cycle of a product, including computer-aided design (CAD), computer-aided engineering (CAE), and topology optimization (TO), taking into account the manufacturing constraints of a specific AM process. The digital thread can improve product quality by avoiding errors in the manual translation of engineering specifications along the product value chain, increase the speed at which new product introductions and engineering changes are transmitted along the product value chain, increase the efficiency of digitally capturing and analyzing data related to product manufacturing, and allow manufacturers to provide new services to customers along with physical products, thereby leveraging the digital data now available on the product.

[0030] refer to Figure 1 , a method 10 for designing a component to be formed by an additive manufacturing process and suitable for an additive manufacturing process according to the teachings of the present disclosure begins with creating a CAD model for the component in step 12. The component may be an automotive component or any structure in which weight reduction is desired. In step 14, the CAD model is converted into a CAE model in the form of a 3D mesh in a CAE environment. In step 16, the material properties of the component are assigned to the CAE model. The material of the component may be metal, ceramic, polymer, composite material, and plastic. In step 18, design requirements are generated, and in step 20, the design requirements are translated into load conditions, boundary conditions, optimization objectives, and design constraints. Steps 12 to 20 constitute a CAD-CAE integration process. In the CAD-CAE integration process, a CAE model with a structural optimization setting is generated.

[0031] Next, in step 22, element density thresholds for voids, solid materials, and lattice cells are established. In step 24, the baseline design of the CAE model is topologically optimized, wherein the structure of the baseline design is optimized based on the element density thresholds to achieve maximum weight reduction and meet the design requirements for performance (e.g., stiffness). Steps 22 and 24 constitute a multi-scale topology optimization process.

[0032] Topology optimization (TO) is a mathematical method for optimizing the layout of materials within a given design space for a given set of loads, boundary conditions, and constraints, with the goal of maximizing the performance of the system. TO can help reduce weight by distributing materials to optimal locations. Multiscale TO processes are used to distribute solid materials, voids, and lattice cells to optimal locations.

[0033] Ideally, there should be only two types of elements in the final design so that the 3D printer can process and manufacture it: "white" elements (0) representing voids and "black" elements (1) representing solid materials. However, existing software tools generate "gray" elements with values ​​between 0 and 1. Traditionally, designers manually set thresholds to classify gray elements as 0 or 1. However, this ad hoc binarization step deviates the result from the global optimization.

[0034] In the multi-scale TO process of the present disclosure, gray elements are not simply classified into 0 or 1. Instead, lattice cells can be used for gray elements. Therefore, in the multi-scale TO process, a 3D mesh structure is generated, which consists of three regions: a void region without material, a solid material region, and an inhomogeneous lattice cell region. These regions are spatially distributed over the entire component according to the load conditions, so that the solid material is distributed in regions of relatively high loads, load paths, or stresses and the lattice cells are distributed in regions of relatively low loads, load paths, or stresses below the solid material regions.

[0035] refer to Figure 2 , two element density thresholds can be used to classify "grey elements" into solid materials, voids, or lattice cells. Elements with a density equal to or higher than 0.9 are classified as "solid". Elements with a density lower than 0.05 are classified as "voids". Elements with a density between 0.05 and 0.9 are classified as "lattice cells".

[0036] refer to Figure 3A , Figure 3B and Figure 3C, three types of lattice cells can be used depending on the shape and density of the elements: 6-bar tetrahedral lattice cells 50 for tetrahedral elements, 16-bar hexahedral lattice cells 52 or 24-bar hexahedral lattice cells 54 for hexahedral elements on the part being designed. These lattice cells have different numbers and diameters of bars 56 and shapes. Therefore, the type and size of the lattice cells 50, 52, 54 used depends on the shape of the elements on the part being designed and also varies with the additive manufacturing process. The diameter of the bars 56 in the same lattice cell can be the same or different and can be determined by an optimization algorithm. Lattice cells with more bars and larger diameter bars can be assigned to elements with higher density. Lattices with fewer bars and smaller diameter bars can be assigned to elements with lower density. For example, a 24-bar hexahedral lattice cell can be selected for an element with a higher density, and a 6-bar tetrahedral lattice can be selected for an element with a lower density. In this multi-scale TO process, the diameter of the lattice bars 56 in the lattice cells 50, 52, 54 is selected / designed without regard to the resolution (ie, voxels) of the AM machine.

[0037] Return to reference Figure 1 After the diameter of the lattice bars 56 in the lattice cells 50, 52, 54 is determined and selected, in step 26, a statistical analysis model is formed, a statistical distribution of the lattice bar diameters is generated, and the diameters of the lattice bars in the lattice cells are statistically analyzed. The lattice size is then adjusted and optimized based on the statistical analysis in step 28. In step 30, the new design with the adjusted and optimized lattice size is verified. Steps 26 to 30 constitute a statistical analysis and lattice size optimization process, which optimizes the diameter of the lattice bars of the lattice cells based on the pixel length (or voxel) of the 3D printer.

[0038] In lattice design, typical TO software cannot consider manufacturing constraints (e.g., the resolution of the AM machine) during the topology optimization process. Therefore, the diameter of the lattice 56 in the lattice cells 50, 52, 54 is designed and determined without considering the resolution of the AM machine, and the diameter may be a value that cannot be printed by a 3D printer with a predetermined pixel length.

[0039] The statistical analysis and lattice size optimization process of the present disclosure is a post-processing tool that generates a final lattice design based on the statistical information of the original TO results. During the statistical analysis process, the diameter of the lattice bars 56 is rounded to an integer, which is a multiple of the pixel length of the 3D printer, so that the final design is suitable for 3D printing. Therefore, the final lattice structure design obtained after the statistical analysis and lattice size optimization process will meet the manufacturing constraints of the specific additive manufacturing process to be used, while maintaining the reduced weight and superior performance of the TO results. The additive manufacturing process can be selected from the group consisting of: selective laser sintering (SLS), stereolithography (SLA), fused deposition modeling (FDM), polymer jetting (PJ), direct metal laser sintering (DMLS), selective layer melting (SLM), continuous liquid phase production (CLIP), layered entity manufacturing (LOM).

[0040] refer to Figure 4 , forming a statistical analysis model to generate a statistical distribution of lattice bar diameters. Based on the statistical distribution of lattice bar diameters, the lattice bars of each lattice are classified into several clusters. The average diameter is assigned to all lattice cells in the same cluster. The diameters of truss elements in the same cluster are very close to each other, and truss elements from different clusters can be easily distinguished by the difference in lattice bar diameter values. The average diameter of the cluster (rounded to the nearest integer that is a multiple of the pixel length) is assigned to all lattice cells in the same cluster. In other words, the average diameter of the cluster is adjusted according to the resolution unit of the additive manufacturing machine and the performance requirements of the component, and the resolution unit is an integer that is equal to the pixel length of the 3D printer or a multiple thereof. After the average diameter is assigned to the lattice cells in the same cluster and a new design is generated, the new design in the form of a 3D topology is simulated and verified in step 30 to ensure that all design requirements are met.

[0041] refer to Figure 5 , after adjusting the average diameter of the lattice cells, a design with an optimal lattice size was generated. The new design that underwent multi-scale topology optimization and lattice size optimization was shown to have a mesh structure with a mass of 0.744 kg, resulting in a 35.1% mass reduction compared to the original design mass of 1.147 kg. The new design also met the design constraint of stiffness, which was measured by the maximum displacement under load, while the original design was overdesigned or heavier than necessary to meet the stiffness requirements.

[0042] Return to reference Figure 1, after the statistical analysis and lattice size optimization process, a new design is generated in STL file (stereolithography file format) in step 32, and the new design is further verified in step 34. A prototype is then generated in step 36. Steps 32 to 36 constitute the CAE-AM integration process. After the CAE file of the best design with the optimized mesh is generated, the optimized mesh output is smoothed, flattened and fixed to meet the A surface requirements.

[0043] refer to Fig. 6A , Figure 6B , Fig. 7A and Figure 7B , showing two CAE files of the two best designs outputted using the optimized mesh. Fig. 6A and Figure 6B A first design is shown in the form of a tetrahedral mesh. Fig. 7A and Figure 7B The second design in the form of voxel grid is shown. In either design, the optimized grid output from CAE is rough. Therefore, the 3D grid topology is smoothed, flattened and fixed to meet the A surface requirements. The CAE-AM integration process needs to hollow out the A surface parts and merge them in the CAE output through a series of Boolean operations. The lattice beam output from CAE needs to be converted into a surface with suitable beams and connection properties. Further change the optimized surface to add additional structural elements required by the specific AM process, such as geometric features. For example, for selective laser sintering (SLS) or stereolithography (SLA), it may be necessary to provide an outlet slot in the designed part to allow unsintered powder or uncured resin to leave the part. For manufacturing methods such as stereolithography (SLA) or direct metal laser sintering (DMLS), low-angle lattice components must be filtered out relative to process constraints to achieve unsupported lattice manufacturing. For fused filament fabrication (FFF) and fused deposition molding (FDM) methods, the lattice structure must be converted into a similar filling density pattern orthogonal to the build plate surface.

[0044] Once the model has been fully prepared and customized for manufacturing, it can be brought back into the CAE environment to confirm that the leveling and geometry edits made have not structurally damaged the design. Finally, the CAE file is converted into an STL file, which is one of the most common file types that can be read by 3D printers and used to manufacture prototypes.

[0045] The method for designing a component to be formed by an additive manufacturing process according to the teachings of the present disclosure successfully integrates computer-aided design (CAD), computer-aided engineering (CAE), topology optimization (TO) and additive manufacturing (AM). The method also improves TO technology and lattice structure design methods by analyzing lattice dimensions and distributing solid materials and lattice units to locations subject to stress / strain. Therefore, the material of the structure can be cleverly redistributed, thereby reducing material consumption and reducing the weight of the component. When the component is an automotive component, the design will contribute to enhanced fuel economy. The structure also accelerates the design of lightweight structures for AM and generates creative complex structural designs with lighter weight and higher performance. The method can help eliminate the cost of mold creation, an economic solution for low-volume component design, resulting in more streamlined and more environmentally friendly manufacturing.

[0046] It should be noted that the present disclosure is not limited to the various forms described and shown as examples. A wide variety of modifications have been described, and more are part of the common knowledge of those skilled in the art. These and other modifications and any replacement by technical equivalents may be added to the description and drawings without departing from the scope of protection of the present disclosure and this patent.

[0047] According to the present invention, there is provided a component formed by an additive manufacturing process, the component having three regions: a void region; a solid material region; and a non-uniform lattice unit region, wherein the regions are spatially distributed throughout the component according to load conditions, such that the solid material is distributed in the region of a first load path and the lattice units are distributed in the region of a second load path, the second load path being lower in magnitude than the first load path.

[0048] According to an embodiment, the lattice cells include 6-lattice tetrahedral lattice cells, 16-lattice hexahedral elements, and 24-lattice hexahedral elements, wherein the type and size of the lattice cells vary with the additive manufacturing process.

[0049] According to an embodiment, the diameters of each lattice bar of the lattice unit are unequal.

[0050] According to an embodiment, a diameter of each bar of the lattice is a function of at least one of a resolution unit and a part performance requirement of the additive manufacturing process.

[0051] According to an embodiment, the material of the component is selected from the group consisting of metals, ceramics, polymers, composite materials and plastics.

[0052] According to the present invention, a method for designing a component formed by an additive manufacturing process includes: generating a 3D mesh topology consisting of three (3) regions: a void region; a solid material region; and a non-uniform lattice unit region, wherein the regions are spatially distributed throughout the component according to load conditions, such that the solid material is distributed in the region of a first load path and the lattice units are distributed in the region of a second load path, the second load path being lower in magnitude than the first load path.

[0053] According to an embodiment, the lattice cells include 6-lattice tetrahedral lattice cells, 16-lattice hexahedral elements, and 24-lattice hexahedral elements, wherein the type and size of the lattice cells vary with the additive manufacturing process.

[0054] According to an embodiment, the diameter of each lattice bar of the lattice cell is optimized based on the load conditions such that the diameters are unequal.

[0055] According to an embodiment, the diameter of each lattice bar of the lattice is adjusted according to at least one of a resolution unit and a component performance requirement of the additive manufacturing process.

[0056] According to an embodiment, the above invention is further characterized by forming a statistical analysis model to generate a statistical distribution of lattice bar diameters, and further classifying the lattice bars of each lattice into clusters, wherein all lattice cells in the same cluster are assigned an average diameter of the cluster.

[0057] According to an embodiment, the average diameter of the clusters is adjusted according to at least one of a resolution unit and a part performance requirement of the additive manufacturing process.

[0058] According to an embodiment, the above invention is also characterized by a verification step for verifying that the 3D mesh topology meets the design requirements.

[0059] According to an embodiment, the above invention is also characterized in that the 3D mesh topology is smoothed, flattened and fixed to meet the A surface requirements.

[0060] According to an embodiment, the above invention is further characterized in that additional structural elements are generated according to the additive manufacturing process.

[0061] According to an embodiment, the above invention is further characterized in that the geometric features are generated according to the additive manufacturing process.

[0062] According to an embodiment, the geometrical feature comprises an exit slot for unsintered powder for a selective laser sintering (SLS) or for uncured resin for a stereolithography (SLA) process.

[0063] According to the present invention, a method for manufacturing a component using an additive manufacturing process includes: manufacturing solid material areas; manufacturing non-uniform lattice unit areas; and leaving void areas without material; wherein the areas are spatially distributed throughout the component according to load conditions, so that the solid material is distributed in the area of ​​a first load path and the lattice units are distributed in the area of ​​a second load path, and the second load path is lower in magnitude than the first load path.

[0064] According to an embodiment, the diameter of each lattice bar of the non-uniform lattice cell is adjusted according to at least one of a resolution unit and a component performance requirement of the additive manufacturing process.

[0065] According to an embodiment, the component is manufactured by different additive manufacturing processes.

[0066] According to an embodiment, the additive manufacturing process is selected from the group consisting of: selective laser sintering (SLS), stereolithography (SLA), fused deposition modeling (FDM), polymer jetting (PJ), direct metal laser sintering (DMLS), selective layer melting (SLM), continuous liquid interphase production (CLIP), and layered object manufacturing (LOM).

Claims

1. A component formed by an additive manufacturing process, the component consisting of three regions: void area; Solid material area; as well as Inhomogeneous lattice cell regions, wherein the regions are spatially distributed throughout the component according to load conditions such that the solid material is distributed in the region of a first load path and the lattice cells are distributed in the region of a second load path, the second load path being lower in magnitude than the first load path; wherein the lattice units include 6-lattice tetrahedral lattice units, 16-lattice hexahedral elements, and 24-lattice hexahedral elements, wherein the type and size of the lattice units vary with the additive manufacturing process; wherein the diameter of each lattice bar of the lattice unit is optimized based on the load condition so that the diameters are unequal; wherein the diameter of each lattice bar of the lattice is adjusted according to at least one of a resolution unit and a component performance requirement of the additive manufacturing process; A statistical distribution of lattice bar diameters is generated based on a statistical analysis model, and the lattice bars of each lattice are classified into clusters, and all lattice cells in the same cluster are assigned an average diameter of the cluster.

2. The component of claim 1, the average diameter of the clusters being adjustable according to at least one of a resolution unit of the additive manufacturing process and a component performance requirement.

3. The component of claim 1 , further comprising additional structural elements generated according to the additive manufacturing process.

4. The component of claim 1 , further comprising geometric features generated according to the additive manufacturing process.

5. The component of claim 1, wherein a material of the component is selected from the group consisting of metals, ceramics, polymers, composites, and plastics.

6. A method of designing a component formed by an additive manufacturing process, the method comprising: Generates a 3D mesh topology consisting of three regions: void area; Solid material area; as well as Inhomogeneous lattice cell regions, wherein the regions are spatially distributed throughout the component according to load conditions such that the solid material is distributed in the region of a first load path and the lattice cells are distributed in the region of a second load path, the second load path being lower in magnitude than the first load path; wherein the lattice units include 6-lattice tetrahedral lattice units, 16-lattice hexahedral elements, and 24-lattice hexahedral elements, wherein the type and size of the lattice units vary with the additive manufacturing process; wherein the diameter of each lattice bar of the lattice unit is optimized based on the load condition so that the diameters are unequal; wherein the diameter of each lattice bar of the lattice is adjusted according to at least one of a resolution unit and a component performance requirement of the additive manufacturing process; The method also includes forming a statistical analysis model to generate a statistical distribution of lattice bar diameters, and further classifying the lattice bars of each lattice into clusters, wherein all lattice cells in the same cluster are assigned an average diameter of the cluster. 7 . The method of claim 6 , wherein the average diameter of the clusters is adjusted according to at least one of a resolution unit and a part performance requirement of the additive manufacturing process. 8 . The method according to claim 6 , further comprising a verification step for verifying that the 3D mesh topology meets design requirements.

9. The method of claim 6, further comprising smoothing, flattening and fixing the 3D mesh topology to meet A-surface requirements.

10. The method of claim 6, further comprising generating additional structural elements according to the additive manufacturing process.

11. The method of claim 6, further comprising generating geometric features according to the additive manufacturing process.

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