Method for providing a procedural instruction for additive manufacturing

Abstract

The invention relates to a method for providing a procedural instruction for the additive manufacturing of a component, with the method steps of establishing and / or providing a first procedural instruction for the additive manufacturing of a first build structure, wherein the first build structure comprises the component and a first supporting structure, wherein the first procedural instruction is established by a first method, establishing a second procedural instruction for the additive manufacturing of a second build structure, wherein the second build structure comprises the component and a second supporting structure, wherein the second procedural instruction is established on the basis of the first procedural instruction, wherein the second procedural instruction is established by a second method and wherein the first method is different from the second method.

Description

[0001] METHOD FOR PROVIDING A PROCESS INSTRUCTION FOR ADDITIVE MANUFACTURING

[0002] The invention relates to a method for providing a process instruction for the additive manufacturing of a component with the process steps of creating and / or providing a first process instruction for the additive manufacturing of a first building structure, wherein the first building structure comprises the component and a first support structure, wherein the first process instruction is created using a first method, and creating a second process instruction for the additive manufacturing of a second building structure, wherein the second building structure comprises the component and a second support structure, wherein the second process instruction is created on the basis of the first process instruction, wherein the second process instruction is created using a second method and wherein the first method is different from the second method.

[0003] State of the art

[0004] 3D printing or additive manufacturing is a comprehensive term for all manufacturing processes in which material is applied layer by layer to create three-dimensional components. The layer-by-layer build-up is computer-controlled from one or more liquid or solid materials according to specifications from a CAD / CAM system. The layers can then be broken down into strips, particularly in direct energy deposition processes. In addition, in so-called hatching, a layer is divided into strips (hatches) or squares and parallel vectors are distributed within them. With powder bed-based technologies, such as selective laser melting, the component is manufactured without further subdivision of the layers. When building up the workpiece layer by layer, a print head or a laser is usually moved horizontally, i.e. in the XY-i plane, and at the same time, strips of material are applied using the print head or laser.Once a layer is completed, the build plate on which the workpiece is being manufactured is usually moved vertically downwards, i.e. in the Z direction, and another layer is started. During the application or melting of the layers, the workpiece may experience problems such as cracking, deformation and an uneven crystal structure, depending on the type of material applied and the set process parameters (e.g. temperature, feed rate). In other cases, this can even lead to the entire manufacturing process having to be stopped. In the prior art, a process plan is usually created based only on the geometric design of a workpiece. If such a process plan is executed, it can lead to a phenomenon that a specific section of the workpiece becomes overheated during a manufacturing process, for example, and it becomes difficult to control the temperature of the workpiece effectively.In addition, in the state of the art in an additive manufacturing process, it is impossible to change and adapt the process plan, especially during the manufacturing process, once a process plan has been completely created.

[0005] It is therefore an object of the invention to provide a method for providing a process instruction for the additive manufacturing of a component, with which an improved process plan for the additive manufacturing of a workpiece is provided.

[0006] The object is achieved by means of the method according to the invention for providing a method instruction for the additive manufacturing of a component according to claim 1. Advantageous embodiments of the invention are set out in the following subclaims.

[0007] The method according to the invention for providing a process instruction for the additive manufacturing of a component has two process steps: In the first process step, a first process instruction for the additive manufacturing of a first building structure is created and / or provided, wherein the first building structure comprises the component and a first support structure, wherein the first process instruction is created using a first method.

[0008] In the second method step, a second process instruction is created for the additive manufacturing of a second build structure, wherein the second build structure comprises the component and a second support structure. The second process instruction is created based on the first process instruction, wherein the second process instruction is created using a second method. According to the invention, the first method is different from the second method.

[0009] A process instruction refers to data provided to an additive manufacturer for the additive production of a build structure. This includes the process parameters for the additive manufacturer and the definition of a tool path. The tool path typically consists of a series of vectors that are traversed by the additive manufacturer. The process instructions thus define a process control that is executed by the additive manufacturer for the additive production of a build structure.

[0010] Additive manufacturing processes within the meaning of this application are processes in which the material from which a build structure is to be produced is added to the build structure during its creation. The build structure is created in its final form, or at least approximately in this form, and then undergoes post-processing. In particular, the build structure to be manufactured has a support structure comprising one or more support points. This support structure is removed during post-processing.

[0011] For manufacturing reasons, the aforementioned 3D printing processes require the use of a support structure to support delicate or overhanging structures during the printing process. These structures would otherwise collapse under the force of gravity. Support structures are also sometimes necessary in metal 3D printing, but for different reasons than in plastic-based additive processes. Here, the risk is less that the model could collapse during printing, but rather to prevent impending warping. For example, thin areas of the model can easily bend.

[0012] The techniques used by an additive manufacturer to produce a part include, for example, extrusion deposition or selective deposition modeling (SDM), techniques such as fused deposition modeling (FDM) and fused filament fabrication (FFF), stereolithography (SLA), polyjet printing (PJP), multijet printing (MJP), selective laser sintering (SLS), selective laser melting (SLM), three-dimensional printing (3DP), techniques such as inkjet printing (CJP), directed energy deposition (DED) and the like.

[0013] Fused filament fabrication (FFF), also known as fused deposition modeling or filament freeform fabrication, is a 3D printing process that uses a continuous filament made of a thermoplastic material. The filament is fed from a large spool through the printer's moving, heated extruder head and deposited onto the growing workpiece. The print head is moved under computer control to define the printed shape. Typically, the head moves in two dimensions to deposit one horizontal plane or layer at a time; the workpiece or print head is then moved vertically a small amount to begin a new layer. The speed of the extruder head can also be controlled to stop and start deposition, creating a discontinuous plane without threads or drips between sections.

[0014] Directed Energy Deposition (DED) refers to a category of additive manufacturing or 3D printing processes in which powder or wire is fed coaxially to an energy source (usually a laser) to form a molten or sintered layer on a substrate. Melt filament printing is currently the most popular method for 3D printing, especially among hobbyists. Other processes such as photopolymerization and powder sintering can produce better results but are significantly more expensive. The 3D printer head, or 3D printer extruder, is a part in additive manufacturing through material extrusion that is responsible for melting or softening the raw material and forming it into a continuous profile.A wide variety of filament materials are extruded, including thermoplastics such as acrylonitrile butadiene styrene (ABS), polylactic acid (PLA), polyethylene terephthalate glycol (PETG), polyethylene terephthalate (PET), high impact polystyrene (HIPS), thermoplastic polyurethane (TPU) and aliphatic polyamides (nylon).

[0015] In this document, the terms "create", "calculate", "calculate", "determine", "generate", "configure", "modify", "transform" and the like are used synonymously unless otherwise stated and preferably refer to actions and / or processes and / or processing steps that change and / or generate data and / or convert the data into other data, wherein the data can be represented or present in particular as physical quantities, for example as electrical impulses.

[0016] The method according to the invention for providing a process instruction for the additive manufacturing of a building structure is computer-aided, wherein the term “computer-aided” is used, for example, in this document in such a way that one computer or multiple computers carry out or carry out at least one process step of the method. Computers can be, for example, personal computers, servers, handheld computer systems, pocket PC devices, mobile radio devices and other communication devices that can process data in a computer-aided manner, as well as processors and other electronic devices for data processing, which can also be connected to form a network. A method within the meaning of the invention is a systematic and targeted procedure for creating a process instruction for the additive manufacturing of a building structure using formalized processes. The formalized processes are defined, for example, in a computer program.

[0017] The method according to the invention creates a first process instruction for the additive manufacturing of a first structural component and a second process instruction for the additive manufacturing of a second structural component. The two structural components have the same component but different support structures. Thus, one and the same component can be manufactured using the first and second process instructions, with the second process instruction being created on the basis of the first process instruction. The first process instruction is optimized using the second process instruction such that the manufactured component exhibits improved residual stress distribution. Both process instructions are generated using different methods, e.g., using different computer programs.

[0018] In a further development of the invention, a method instruction comprises a geometric start (x,y,z) and a geometric end point (x,y,z) for each individual vector (exposure vector).

[0019] In an optional development according to the invention, the laser power and / or the laser speed are included in a process instruction. In a further embodiment of the invention, a process instruction has one or more elements of the following group of parameters: type of vector (fill, contour vector; overhang vector, surface vector), polygon that describes the outer boundaries of the part, start / end time of each vector, pause times between the vectors (forced (e.g.) for cooling or due to optical / mechanical conditions), pause times between layers, coater times and information, build plate temperature, assignment of which vector is written by which laser, areas that the individual lasers can reach, continuous or pulsed vector, focus of the laser and which laser mode (per vector), rarely: circular movements of the laser (wobble), information about the gas used and its direction of flight in the build chamber and / or information and / or instructions about the layer thickness or information and / or instructions to lower the build plate.

[0020] In a further embodiment of the invention, the process instruction comprises one or more elements of the following group of parameters: an instruction for initialization and setup, an instruction for controlling the energy source with commands for controlling the laser, electron beam or plasma arc, an instruction for switching the energy source on and / or off and / or adjusting its power, instructions for material supply and nozzle control with commands for controlling the material flow rate and / or commands for controlling the nozzle temperature, instructions for movement and path control with the movement control of the nozzle and / or the workpiece, optionally specifying the speed, direction and / or change of direction, the course (straight or curved line) and / or specifying the end point and / or starting point and / or the starting position (often used for setting the starting position of the material deposition),Instructions for layering and deposition patterns with specific commands for controlling layer thickness and deposition pattern and / or Z-axis adjustments for each new layer; instructions for cooling and / or temperature management and / or commands for cooling systems and / or heat management; instructions for advanced control of, for example, the gas flow in the deposition head, the energy density, and / or the deposition rate; and / or instructions for process end with commands for controlling the movement of the nozzle and / or the workpiece to a safe end position and / or commands for switching off the energy source and material supply. Optionally, the process instruction includes instructions for applying the binder material.

[0021] In a further development of the invention, the first method instruction comprises the irradiation path of an energy beam, the exposure vectors, the process parameters of the beam source and / or the process parameters for influencing the energy input into the building structure.

[0022] Process parameters are all variables that influence the manufacturing process using additive manufacturing. Process parameters are all variables that influence the process. The additive manufacturer requires process parameters to produce the component, e.g., the height of the layers to be produced, the orientation of the vectors, i.e., the direction and length of the path that the tool describes on the surface of the component to be manufactured. The method according to the invention creates a first process instruction and a second process instruction for a specific material intended for processing by additive manufacturing. The process parameters used depend on the additive manufacturer used to produce the component.

[0023] The tool path typically consists of a series of vectors that are traversed by the additive manufacturer. The process instructions thus define a process control that is executed by the additive manufacturer for additive manufacturing.

[0024] The warmer the already produced structure is, the slower the heat dissipation in the build occurs. The vector length influences the temperature development in that the repeated heating of neighboring points is spaced further apart due to the parallel position of successively exposed vectors. Another important factor is the mass distribution around the vectors, as this directly influences heat dissipation and thus the risk of overheating.

[0025] In a further embodiment of the invention, the process parameters for influencing the energy input into the build structure include the power of the energy beam, the irradiation times of individual vectors, the pause times between the irradiation times of individual vectors, the traversing speed of the energy beam, the hatch distance between the vectors, the vector sequence, the vector length, and / or the vector orientation. In this way, overheating in vulnerable areas of the component can be prevented. Process parameters are understood to be all variables that influence the manufacturing process using additive manufacturing.

[0026] In a further embodiment of the invention, the process parameters for influencing the energy input into the build structure depend on the material of the build structure. Different materials of the build structure have different material properties, such as heat capacity, thermal conductivity, melting temperature, and the reflection coefficient of the powder used. Other material properties include material stiffness, material thickness, material fatigue, material elongation at break, material elastic modulus, material compression modulus, and material shear modulus. A component to be manufactured often has thin-walled or overhanging structures. In these areas, the body of the build structure provides a significantly smaller local thermal capacity, so that the build structure can overheat locally when using standard process parameters.

[0027] In a further embodiment of the invention, data from the first process instruction are read in and / or entered to create the second process instruction, wherein the data from the first process instruction include the build structure geometry, the component geometry, the irradiation path of an energy beam, the exposure vectors and / or the process parameters of the beam source and / or the process parameters for influencing the energy input into the build structure. The first process instruction provides basic data and process parameters for the additive manufacturing of a build structure, which forms the basis for creating a second process instruction. By means of the second process instruction, a build structure can be produced which does not overheat in particularly vulnerable areas during the manufacturing process and has a lower residual stress distribution in the cooled and post-processed state, which, for example,relevant in the manufacture of turbine blades. In a further development of the invention, the data from the first process instruction is read in or loaded from an external source. The external source is a storage unit, e.g., a database, located remotely from the unit that provides the first process instruction.

[0028] In a further embodiment of the invention, machine data from the additive manufacturer are read in and / or entered and / or used to create the second process instruction, wherein the machine data includes the possible process parameters of the additive manufacturer, the possible travel speeds, and the possible travel paths of the component to the additive manufacturer. Machine data differs for different additive manufacturers and is therefore used to create the second process instruction. At the same time, it is possible to create second process instructions for different additive manufacturers; the method according to the invention can therefore be applied to different additive manufacturers.

[0029] In a further embodiment of the invention, the component data are read in and / or entered and / or used to create the second process instruction, wherein the component data comprise the geometry of the build structure, the geometry of the component and / or material data, and wherein the material data comprise the phases, the concentration of the phases, the microstructure, the mechanical properties, the melting temperature and / or the boiling temperature. A build structure to be manufactured often contains thin-walled or overhanging structures. In these areas, the body provides a significantly smaller local thermal capacity, so that the structure can overheat locally when using standard process parameters. This leads, for example, to undesirably large melt pools, which hinder the manufacturing process due to the formation of large melt beads.For all possible combinations of process and material parameters, corresponding data must be stored in the database. For individual applications, the appropriate data must be retrieved from the database and taken into account when calculating temperature development.

[0030] In a further embodiment of the invention, simulation data is read in and / or input and / or used to create the second process instruction, wherein the simulation data comprises calculated data determined based on a model and set or predefined parameters. The simulation data includes data about a structural component in which shrinkage and the formation of structural stresses are taken into account during shaping by producing a structural component geometry modified by the simulation method, which assumes the desired structural component geometry due to the stresses and shrinkages.

[0031] In a further embodiment of the invention, experimental data are read in and / or input and / or used to create the second process instruction, wherein the experimental data comprise experimentally determined data. The experimental data comprise data of a building structure that was created in-situ in real time and / or in previous manufacturing processes. With the experimental data, the creation of the second process instruction can include data acquired based on real, non-simulated manufacturing processes.

[0032] In a further embodiment of the invention, process parameters of the second process instruction are determined using an ML and / or AI algorithm to create the second process instruction. The ML and / or AI algorithm can use different methods to determine the process parameters.

[0033] The possible ML and / or AI algorithms that can be used are described in the following paragraphs. Random Forest Regression is a machine learning method based on ensemble learning. An ensemble of multiple decision trees is combined and used for regression. This is a supervised learning approach.

[0034] Gradient boosted trees is another ensemble learning technique that can be applied to regression and classification. It is classified as supervised learning.

[0035] Deep learning (also known as multi-layer learning or in-depth learning) is a method of machine learning. Most deep learning algorithms are deep neural networks (DNNs). They consist of many layers of linear and nonlinear processing units, the artificial neurons. The more neurons and layers a neural network contains, the more complex the data it can represent.

[0036] Another type of deep learning algorithm is decision trees (Random Decision Forests, or RDFs). They also consist of many layers, but instead of neural structures, RDFs are constructed from decision trees and output a statistical average (mode or mean) of the predictions of the individual trees.

[0037] Deep learning is used wherever large amounts of data need to be analyzed for patterns and trends. Within AI, this happens, for example, in the following areas: facial, object, and speech recognition.

[0038] A convolutional neural network (CNN or ConvNet) is an artificial neural network. It is a concept in the field of machine learning inspired by biological processes. Convolutional neural networks are used in numerous artificial intelligence technologies, primarily in the machine processing of image or audio data.

[0039] Recurrent or feedback neural networks are neural networks that, in contrast to feedforward networks, are characterized by connections between neurons in one layer and neurons in the same or a previous layer. In the brain, this is the preferred wiring configuration for neural networks, particularly in the neocortex. In artificial neural networks, the recurrent wiring of model neurons is used to discover temporally encoded information in the data. Examples of such recurrent neural networks are the Elman network, the Jordan network, the Hopfield network, and the fully connected neural network.

[0040] In a further embodiment of the invention, the ML and / or AI algorithm uses empirical data to determine the process parameters of the second process instruction, wherein the empirical data comprises machine data, component data, simulation data, and / or experimental data. The empirical data comprises data that was recorded and created using one or more previous additive manufacturing processes for components or structures, as well as the process instructions specific to each component. This data is stored in a database. For each individual application, the appropriate data must be retrieved from the database and used in calculating the temperature development using an ML and / or AI algorithm.

[0041] In one development of the invention, the empirical data comprises machine data from different additive manufacturers. In a further embodiment of the invention, the different additive manufacturers comprise additive manufacturers of different designs. In a further embodiment of the invention, the different additive manufacturers use different CAM processes to manufacture a component. The machine data comprises the possible process parameters of the additive manufacturer, the possible travel speeds, and the possible travel paths of the component to the additive manufacturer. Machine data is different for different additive manufacturers and is therefore used to create the second process instruction. At the same time, it is possible to create second process instructions for different additive manufacturers; the process according to the invention can therefore be applied to different additive manufacturers.

[0042] In a further embodiment of the invention, the empirical data comprises data from different CAM processes, wherein CAM processes include laser and / or electron beam powder bed fusion, direct energy deposition (DED), binder jetting, fused filament fabrication (FFF), melt filament printing, and / or other non-abrasive computer-aided manufacturing processes that rely on a tool path with process parameters assigned to it. Such empirical data is used to create the second process instruction; such a second process instruction can therefore be used for different CAM processes.

[0043] In an advantageous embodiment of the invention, the second process instruction comprises modified values ​​for the energy beam power, the irradiation times of individual vectors, the pause times between the irradiation times of individual vectors, the traversing speed of the energy beam, the increase in the hatch distance between the vectors, the vector sequence, the vector length, and / or the vector orientation compared to the first process instruction. Using the second process instruction, a structure can be produced that does not overheat in particularly vulnerable areas during the manufacturing process and exhibits a lower residual stress distribution in the cooled and post-processed state. The manufactured structure is therefore better protected against local overheating.

[0044] In a further embodiment of the invention, the structural structure and / or the component manufactured according to the second process instruction has different mechanical characteristics compared to a structural structure and / or a component manufactured according to the first process instruction. In a further aspect of the invention, the mechanical characteristics include the residual stress distribution in the structural structure and / or the component. Advantageously, the component manufactured according to the second process instruction has a minimized residual stress distribution. The mechanical characteristics of the component are significantly improved compared to previously known processes. By means of the process according to the invention, local overheating is avoided, the quality of the finished product is increased, and the production yield is increased by producing less scrap.

[0045] In a further embodiment of the invention, during the manufacturing process, a modified residual stress distribution is generated in the structural member manufactured according to the second process instruction and / or in the component manufactured according to the second process instruction compared to a structural member manufactured according to the first process instruction and / or a component manufactured according to the first process instruction. Advantageously, the component manufactured according to the second process instruction has a minimized residual stress distribution. The mechanical properties of the component are significantly improved compared to previously known processes. By means of the process according to the invention, local overheating is avoided, the quality of the finished product is increased, and the production yield is increased by producing less scrap.

[0046] In a further embodiment of the invention, the structural member manufactured according to the second method instruction has a different geometry than a structural member manufactured according to the first method instruction. A geometry within the meaning of the invention is a spatial arrangement and includes properties such as angle, thickness and structure of the structural member. In a development of the invention, the changed geometry includes the geometry of the component. In a further aspect of the invention, the changed geometry includes the geometry of the support structure. Preferably, the structural member manufactured according to the second method instruction has a support structure whose geometry is different from a structural member manufactured according to the first method instruction in such a way that the support structure has different attachment points on the component, such that the residual stress distribution in the manufactured component is changed.

[0047] In a further embodiment of the invention, the first method for creating the first procedural instruction comprises the use of first software, and the second method for creating the second procedural instruction comprises the use of second software, wherein the first software is different from the second software. The formalized sequences of the two different methods are implemented and processed using different software. In a further embodiment of the invention, the method executed by the first software is different from the method executed by the second software. The second software uses an ML and / or AI algorithm to create the second procedural instruction that is different from the first software used to create the first procedural instruction. The first software optionally does not use an ML and / or AI algorithm.

[0048] In a further embodiment of the invention, the first method for creating the first procedural instruction is executed on a first computer unit, and the second method for creating the second procedural instruction is executed on a second computer unit, wherein the first computer unit is different from the second computer unit. A computer unit within the meaning of the invention comprises all electronic devices with data processing properties. A computer unit is thus, for example, a personal computer, server, handheld computer system, pocket PC device, mobile radio device, and other communications device that can process data with computer support, as well as processors and other electronic devices for data processing, which can also be connected to a network. A computer unit also has a storage unit or is connected to a storage unit.The two different computer units preferably also differ in their location and, particularly, in the access rights that a user has to the computer units.

[0049] In a further embodiment of the invention, the first method accesses a first set of empirical data to create the first process instruction, and the second method accesses a second set of empirical data to create the second process instruction, wherein the first set of empirical data is different from the second set of empirical data. The first set of empirical data comprises data that was recorded and created using one or more previous additive manufacturing processes for components or build structures, as well as the process instructions specific to each component. The empirical data includes machine data of the additive manufacturer for which the first process instruction is to be created, as well as component data, simulation data of the temperature distribution in the build structure during the manufacturing process, and / or experimental data.The second set of empirical data includes the additive manufacturer's machine data, component data, simulation data and / or experimental data to determine the process parameters of the second process instruction.

[0050] In a further embodiment of the invention, the first set of experience data is stored on a first storage device and the second set of experience data is stored on a second storage device, wherein the first storage device is different from the second storage device. In the context of the invention, a storage device is understood to mean, for example, a computer-readable memory in the form of a random-access memory (RAM) or a hard disk. Cloud storage is also possible.

[0051] In a further embodiment of the invention, the additive manufacturing of a component comprises CAM processes, wherein CAM processes include laser and / or electron beam powder bed fusion, direct energy deposition (DED), binder jetting, and / or other non-abrasive computer-aided manufacturing processes based on a tool path with process parameters assigned to it. The method according to the invention for creating a process instruction and the created process instruction can therefore be used for different CAM processes.

[0052] Embodiments of the method according to the invention for providing a process instruction for the additive manufacturing of a component are shown in a simplified schematic form in the drawings and are explained in more detail in the following description.

[0053] They show:

[0054] Fig. 1: State-of-the-art method for providing a

[0055] Procedural instruction

[0056] Fig. 2: Inventive method for providing a procedural instruction

[0057] Fig. 3: Inventive method for providing a procedural instruction, two different methods

[0058] Fig. 4: Inventive method for providing a process instruction, two different computer units

[0059] Fig. 5: Inventive method for providing a method instruction, separate computer units and separate software

[0060] Fig. 6: Flowchart of the method according to the invention for providing a method instruction, separate computer units

[0061] Fig. 7: Flowchart of the method according to the invention for providing a method instruction, separate computer units and separate software

[0062] Fig. 1 shows an embodiment of a method for providing a process instruction, as is known from the prior art. The starting point for implementing additive manufacturing is a description of the workpiece using a data set. Using 3D modeling software (e.g., a CAD program), the data set for the structural design of the component to be manufactured is created. The data set contains the three-dimensional data for processing for production using the additive manufacturing process.

[0063] Subsequently, preprocessing 110 takes place on the build platform in such a way that the data set comprises a volume model of the component to be manufactured and is exported in another form that represents the self-contained surface geometry of the object. A manufacturing data set is generated from the data set, which contains a preparation of the workpiece's geometry in layers or slices suitable for additive manufacturing. This data transformation is referred to as slicing 120.

[0064] In addition, the additive manufacturer requires additional process parameters and tool paths for production, e.g., the height of the layers to be produced, the orientation of the writing vectors, i.e., the direction and length of the path. These process parameters and tool paths are generated in the following process step 130 and sent to the additive manufacturer 300a / b. In the actual production process M, the structure described using CAD is additively manufactured layer by layer in the additive manufacturer using CAM.

[0065] An embodiment of the method according to the invention for providing a process instruction is shown in Fig. 2. In this and all subsequent embodiments, a process instruction is created to produce a build structure using directed energy deposition (DED). In DED, a powder or wire is fed coaxially to a laser to form a molten or sintered layer on a substrate. Support structures are often necessary in DED to secure the parts to the build plate and to secure overhangs.

[0066] First, the workpiece is 3D modeled using a dataset created using a CAD program. This is followed by preprocessing 110 on the build platform, followed by slicing 120. In the next process step, a first process instruction is generated 100, with the data of the first process instruction including the build structure geometry, the component geometry, and the process parameters for influencing the energy input into the build structure.

[0067] To create a second process instruction 200, these data from the first process instruction are read in 220 and used to create 200 the second process instruction. The second process instruction is sent to the additive manufacturer 300a / b, and the building structure to be manufactured is additively manufactured M using the second process instruction.

[0068] Fig. 3 shows an embodiment of the method according to the invention, wherein the first method instruction is created 100 using a first method PROG1, and the second method instruction is created 200 using a second method PROG2 that is different from the first method PROG1. The first method PROG1 and the second method PROG2 are formalized processes defined in a first software program PROG1 and a second software program PROG2, respectively. The two software programs PROG1 and PROG2 are different from each other.

[0069] First, the workpiece is also 3D modeled using a data set created using a CAD program. This is followed by preprocessing 110 on the build platform using the first method PROG1, followed by slicing 120. In the following process step, a first process instruction is also generated 100 using the first method PROG1, wherein the data of the first process instruction includes the build structure geometry, the component geometry, and the process parameters for influencing the energy input into the build structure. These data and process parameters depend on the material of the build structure and on the CAM process used by the additive manufacturer to manufacture the build structure or component. For this purpose, the first method PROG1 accesses 140 a first set of empirical data stored on a first storage device DB1.The first set of empirical data comprises data collected and created using one or more previous additive manufacturing processes for components or build structures, as well as the process instructions specific to each component. The empirical data includes machine data from the additive manufacturer for which the first process instruction is to be created, as well as component data, simulation data of the temperature distribution in the build structure during the manufacturing process, and / or experimental data.

[0070] The data and process parameters of the first process instruction created using the first method PROG1 are read in by the second method PROG2 to create 200 the second process instruction.

[0071] Furthermore, to create 200 the second process instruction, machine data of the additive manufacturer used to manufacture M the building structure or component are read in and / or entered 210 and used to create 200 the second process instruction. The machine data includes the possible process parameters of the additive manufacturer, the possible travel speeds, and the possible travel paths of the component to the additive manufacturer.

[0072] Likewise, component data is read in and / or entered 210 to create 200 the second process instruction and used for the creation 200 of the second process instruction. The component data includes the geometry of the structure, the geometry of the component, and / or material data, wherein the material data includes the phases and the concentration of the phases at a given temperature profile, the microstructure, the mechanical properties, the melting temperature, and / or the boiling temperature.

[0073] In addition, simulation data are read in and / or entered 210 to create 200 the second procedural instruction. The simulation data comprise calculated data that was determined on the basis of a model and entered or specified parameters.

[0074] In addition, experimental data are read in and / or entered 210 to create 200 the second process instruction. The experimental data include experimentally determined data and process parameters that are determined in real time during the manufacturing process M of the building structure and / or were determined from previous manufacturing processes.

[0075] Machine data of the additive manufacturer, component data, simulation data and experimental data are stored on a second storage device DB2 and are loaded from this to create 200 the second process instruction.

[0076] The second process instruction contains process parameters that are advantageously determined using an ML algorithm. The ML algorithm uses empirical data to determine the process parameters of the second process instruction, wherein the empirical data includes the machine data of the additive manufacturer, component data, simulation data, and / or experimental data stored on the second storage device DB2. The second process instruction is sent to the additive manufacturer 300a / b, and the building structure to be produced is additively manufactured M using the second process instruction.

[0077] A further embodiment of the method according to the invention is shown in Fig. 4. Here, the first method instruction is created 100 on a first computer unit COM P1 and the second method instruction is created 200 on a second computer unit COMP2.

[0078] First, a 3D model of the workpiece is created on the first computer unit COMP1 using a dataset created using a CAD program. This is followed by preprocessing 110 on the build platform, followed by slicing 120. In the next process step, a first process instruction is generated 100, wherein the data of the first process instruction includes the build structure geometry, the component geometry, and the process parameters for influencing the energy input into the build structure.

[0079] To create 200 a second process instruction, these data from the first process instruction are read in 220 by the second computer unit COMP2 and used to create 200 the second process instruction. The second process instruction is sent 300a / b to the additive manufacturer, and the building structure to be manufactured is additively manufactured M using the second process instruction.

[0080] Fig. 5 shows the preferred embodiment of the method according to the invention. Here, the first method instruction is created 100 on a first computer unit COMP1 using a first method PROG1. The second method instruction is created 200 on a second computer unit COMP2 using a second method PROG2. The first computer unit COMP1 comprises the first storage device DB1, and the second computer unit COMP2 comprises the second storage device DB2. In each case, the first method PROG1 is different from the second method PROG2, the first computer unit COMP1 is different from the second computer unit COMP2, and the first storage device DB1 is different from the second storage device DB2.

[0081] First, the workpiece is also 3D modeled using a data set created using a CAD program. This is followed by preprocessing 110 on the build platform using the first method PROG1, followed by slicing 120. In the following process step, a first process instruction is generated 100 on the first computer unit COMP1, also using the first method PROG1. The data of the first process instruction includes the build structure geometry, the component geometry, and the process parameters for influencing the energy input into the build structure. These data and process parameters depend on the material of the build structure and on the CAM process used by the additive manufacturer to manufacture the build structure or component. For this purpose, the first method PROG1 accesses 140 a first set of empirical data stored on a first storage device DB1.The first set of empirical data comprises data collected and created using one or more previous additive manufacturing processes for components or build structures, as well as the process instructions specific to each component. The empirical data includes machine data from the additive manufacturer for which the first process instruction is to be created, as well as component data, simulation data of the temperature distribution in the build structure during the manufacturing process, and / or experimental data.

[0082] The data and process parameters of the first process instruction created using the first method PROG1 are read into the second computer unit COMP2 by the second method PROG2 to create the second process instruction. Machine data of the additive manufacturer, component data, simulation data, and experimental data are stored on a second storage device DB2 and are loaded from it to create the second process instruction 200.

[0083] The second process instruction contains process parameters that are also determined using an ML algorithm. The ML algorithm uses empirical data to determine the process parameters of the second process instruction, wherein the empirical data includes the additive manufacturer's machine data, component data, simulation data, and / or experimental data stored on the second storage device DB2.

[0084] In this and all further embodiments, an ML and / or AI algorithm that uses reinforcement learning is used to create 200 the second procedural instruction. Reinforcement learning or reinforcement learning (RL) refers to a series of machine learning methods in which an agent independently learns a strategy to maximize received rewards. The agent is not shown which action is best in which situation; instead, it receives a reward, which can also be negative, at specific times through its interaction with its environment. Other possibilities include the use of an ML and / or AI algorithm that uses supervised learning or unsupervised learning, or intermediate stages of supervised learning or unsupervised learning. Deep learning can also be used.

[0085] The second process instruction is sent to the additive manufacturer 300a / b, and the build structure to be manufactured is additively manufactured using the second process instruction M.

[0086] Fig. 6 and Fig. 7 show embodiments of a flow chart of the method 400 according to the invention. First and second method instructions are created 100, 200 on separate and different computer units COMP1, COMP2 (Fig. 6).

[0087] First, a 3D model of the workpiece is created using a data set created using a CAD program. In this and the following embodiment, the CAD program is executed on a computer unit different from the first computer unit COMP1 and the second computer unit COMP2. The CAD model contains data describing the structure to be manufactured. The data is provided in standardized file formats, for example, as an STL file (STL: Standard Tessellation Language). This CAD data is read by the first computer unit COMP1.

[0088] This is followed by preprocessing 110 on the build platform, followed by slicing 120. In the next process step, a first process instruction is generated 130, which includes the build structure geometry, the component geometry, and the process parameters for influencing the energy input into the build structure. These process steps are executed using a first method PROG1, i.e., a first computer program on the first computer unit COMP1 (Fig. 7).

[0089] A first set of empirical data is then loaded 140 by the first computer unit COMP1 from a first database DB1, which is stored on a first storage device DB1. In this and the following exemplary embodiment, the first storage device DB1 is arranged in the first computer unit COMP1. The first set of empirical data comprises data that was recorded and created using one or more previous additive manufacturing processes for components or building structures, as well as the process instructions specific to each component. The empirical data includes machine data of the additive manufacturer for which the first process instruction is to be created. Using this empirical data, the first process instruction is created 150 by generating the process parameters and tool paths of the additive manufacturer.

[0090] Depending on the additive manufacturer's CAM method, the first process instruction includes the irradiation path of an energy beam, the exposure vectors, the process parameters of the beam source, and / or the process parameters for influencing the energy input into the build structure. The process parameters for influencing the energy input into the build structure include the power of the energy beam, the irradiation times of individual vectors, the pause times between the irradiation times of individual vectors, the traversing speed of the energy beam, the hatch distance between the vectors, the vector sequence, the vector length, and / or the vector orientation. The process parameters for influencing the energy input into the build structure depend on the material of the build structure.

[0091] Optionally, this first process instruction is sent to an additive manufacturer 300a / b, and the build structure can be manufactured based on the first process instruction. Using the first process instruction, a first build structure—i.e., a first component with a first support structure—can be manufactured. Advantageously, a second build structure that differs from the first build structure can be manufactured using the second process instruction.The structural component manufactured using the second process instruction has modified mechanical characteristics compared to a structural component manufactured using the first process instruction and / or a component manufactured using the first process instruction. The mechanical characteristics of the structural component manufactured using the second process instruction include, in particular, modified, in particular minimized, distortion and improved residual stress distribution compared to the structural component manufactured using the first process instruction. The structural component manufactured using the second process instruction therefore has a modified geometry, particularly of the support structure, compared to the structural component manufactured using the first process instruction.

[0092] For this purpose, the process parameters for influencing the energy input into the build structure, the irradiation path of an energy beam, the exposure vectors, and the process parameters of the beam source of the first process instruction are read in 220 by a second computer unit COMP2, wherein the first computer unit COMP1 and the second computer unit COMP2 are different from each other. In addition, machine data of the additive manufacturer, component data, simulation data, and experimental data are read in and / or entered 210, which are stored on a second storage device DB2.

[0093] The second process instruction contains process parameters that are also determined 230 using an ML algorithm. The ML algorithm uses empirical data to determine 230 the process parameters of the second process instruction, wherein the empirical data comprises the machine data of the additive manufacturer, component data, simulation data, and / or experimental data stored on the second storage device DB2. This is followed by a query as to whether, due to the process parameters determined using the ML algorithm, less distortion and, in particular, improved residual stress distribution in the structural component to be manufactured can be achieved. Process steps 220 to 240 are executed using a second method PROG2, i.e., a second computer program on the second computer unit COMP2 (Fig. 7).The process parameters determined by the ML algorithm are used in further iterations of the second method as starting values ​​for the application of an ML algorithm until a minimum of the residual stress distribution in the structure to be manufactured is determined.

[0094] Alternatively, the ML algorithm is used to determine a predictive model of the distortion and residual stress distribution in the structure to be manufactured using the empirical data 220 loaded from the second database DB2. This predictive model is used by the second method PROG2 as the starting value for optimization algorithms. Using the optimization algorithms, process parameters of the second process instruction are optimized using process steps 220 to 240 until a minimized distortion and optimized residual stress distribution in the structure to be manufactured are determined.

[0095] The second process instruction therefore has process parameters with which a structure with minimized distortion and improved residual stress distribution can be produced.

[0096] The second process instruction is sent to the additive manufacturer 300a / b, and the build structure to be manufactured is additively manufactured using the second process instruction M.

[0097] By means of the method 400 according to the invention, a method instruction for the additive manufacturing of a building structure is provided, with which a building structure can be produced using various CAM methods. The CAM methods include laser and / or electron beam powder bed fusion, direct energy deposition (DED) binder jetting, and / or other non-abrasive computer-aided manufacturing methods that are based on a tool path with process parameters assigned to it.

[0098] B EZ UG S CHARACTERS LIST

[0099] CAD Creating a CAD model

[0100] COMP1 First computer unit

[0101] COMP2 Second computer unit

[0102] PROG1 First Software

[0103] PROG2 Second Software

[0104] DB1 First storage device

[0105] DB2 Second Storage Facility

[0106] M Execution of the process instruction / Additive manufacturing of the

[0107] component

[0108] 100 Creating the first procedural instruction

[0109] 110 Preprocessing on build platform / in process chamber

[0110] 120 slices

[0111] 130 Generation of process parameters and tool paths

[0112] 140 Reading data from the first database

[0113] 150 Generation of process parameters and tool paths using data from the first database

[0114] 200 Creating the second procedural instruction

[0115] 210 Reading data from a second database

[0116] 220 Reading data from the first procedural instruction

[0117] 230 Creating the second procedural instruction using the data from the first procedural instruction and applying an ML algorithm

[0118] 240 Query whether reduced distortion and improved residual stress distribution have been achieved in the structure to be manufactured

[0119] 250 Sending the second process instruction a / b Sending the second process instruction to the additive manufacturer Procedure for providing a process instruction for the additive manufacturing of a component

Claims

PATENT CLAIMS 1. Method (400) for providing a process instruction for the additive manufacturing (M) of a component with the process steps: • Creating and / or providing (100) a first process instruction for additive manufacturing (M) of a first construction structure, wherein the first construction structure comprises the component and a first support structure, wherein the first process instruction is created (100) using a first method, • Creating (200) a second process instruction for additive manufacturing (M) of a second construction structure, wherein the second construction structure comprises the component and a second support structure, wherein the second process instruction is created (200) on the basis of the first process instruction, wherein the second process instruction is created (200) using a second method, wherein the first method is different from the second method.

2. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to claim 1, characterized in that the first process instruction comprises the irradiation path of an energy beam, the exposure vectors, the process parameters of the beam source and / or the process parameters for influencing the energy input into the building structure.

3. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to claim 2, characterized in that the process parameters for influencing the energy input into the building structure include the power of the energy beam, the irradiation times of individual vectors, the pause times between the irradiation times of individual vectors, the travel speed of the energy beam, the hatch distance between the vectors, the vector sequence, the vector length and / or the vector orientation.

4. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to claim 2 or 3, characterized in that the process parameters for influencing the energy input into the building structure depend on the material of the building structure.

5. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to one or more of the preceding claims, characterized in that for the creation (200) of the second process instruction, data from the first process instruction are read in and / or input (220), wherein the data from the first process instruction comprise the build structure geometry, the component geometry, the irradiation path of an energy beam, the exposure vectors and / or the process parameters of the beam source and / or the process parameters for influencing the energy input into the build structure.

6. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to claim 5, characterized in that the data from the first process instruction are read in (220) from an external source or loaded from an external source. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to one or more of the preceding claims, characterized in that machine data of the additive manufacturer are read in and / or entered (210) for the creation (200) of the second process instruction and / or are used for the creation (200) of the second process instruction, wherein the machine data comprise the possible process parameters of the additive manufacturer, the possible travel speeds, and the possible travel paths of the component to the additive manufacturer.Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to one or more of the preceding claims, characterized in that for the creation (200) of the second process instruction the component data are read in and / or entered (210) and / or for the creation (200) of the second. Process instruction can be used, wherein the component data comprise the geometry of the building structure, the geometry of the component and / or material data, wherein the material data comprise the phases, the concentration of the phases, the microstructure, the mechanical properties, the melting temperature and / or the boiling temperature.

9. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to one or more of the preceding claims, characterized in that for the creation (200) of the second process instruction, simulation data is read in and / or entered (210) and / or for the creation (200) of the second procedure instruction, where the simulation data comprises calculated data determined on the basis of a model and input or specified parameters.

10. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to one or more of the preceding claims, characterized in that experimental data are read in and / or input and / or used for the creation (200) of the second process instruction, wherein the experimental data comprise experimentally determined data.

11. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to one or more of the preceding claims, characterized in that for the creation (200) of the second process instruction, process parameters of the second process instruction are determined using an ML and / or AI algorithm.

12. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to claim 11, characterized in that the ML and / or AI algorithm uses empirical data to determine the process parameters of the second process instruction, wherein the empirical data comprises machine data, component data, simulation data and / or experimental data.

13. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to claim 12, characterized in that the empirical data comprise machine data from different additive manufacturers.

14. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to claim 13, characterized in that the different additive manufacturers are additive manufacturers of different designs.

15. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to claim 13 or 14, characterized in that the different additive manufacturers use different CAM methods for manufacturing (M) a component.

16. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to one or more of claims 12 to 15, characterized in that the empirical data comprise data from different CAM processes, wherein CAM processes comprise laser and / or electron beam powder bed fusion, direct energy deposition (DED) binder jetting and / or other non-abrasive computer-aided manufacturing processes that are based on a tool path with process parameters assigned to them.

17. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to one or more of the preceding claims, characterized in that the second process instruction comprises, compared to the first process instruction, changed values ​​of the power of the energy beam, the irradiation times of individual vectors, the pause times between the irradiation times of individual vectors, the travel speed of the energy beam, the increase in the hatch distance between the vectors, the vector sequence, the vector length, and / or the vector orientation.

18. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to one or more of the preceding claims, characterized in that the structural element manufactured according to the second process instruction and / or the component manufactured according to the second process instruction has mechanical characteristics which are different from those of a structural element manufactured according to the first process instruction and / or a component manufactured according to the first process instruction.

19. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to claim 18, characterized in that the mechanical characteristics include the residual stress distribution in the structural design and / or the component.

20. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to one or more of the preceding claims, characterized in that during the manufacturing process (M) in the second In the structural structure manufactured according to the first procedural instruction and / or in the component manufactured according to the second procedural instruction, a different residual stress distribution is generated compared to a structural structure manufactured according to the first procedural instruction and / or a component manufactured according to the first procedural instruction.

21. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to one or more of the preceding claims, characterized in that the building structure manufactured according to the second process instruction has a modified geometry compared to a building structure manufactured according to the first process instruction.

22. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to claim 21, characterized in that the changed geometry comprises the geometry of the component.

23. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to claim 21 or 22, characterized in that the changed geometry comprises the geometry of the support structure.

24. Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to one or more of the preceding claims, characterized in that The first method for creating the first process instruction comprises using a first piece of software (PROG1), and the second method for creating the second process instruction comprises using a second piece of software (PROG2), wherein the first software (PROG1) is different from the second software (PROG2). A method (400) for providing a process instruction for additive manufacturing (M) of a component according to claim 24, characterized in that the method executed by the first software (PROG1) is different from the method executed by the second software (PROG2).Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to one or more of the preceding claims, characterized in that the first method for creating (100) the first process instruction is executed on a first computer unit (COMP1) and the second method for creating (200) the second process instruction is executed on a second computer unit (COMP2), wherein the first computer unit (COMP1) is different from the second computer unit (COMP2). Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to one or more of the preceding claims, characterized in that. the first method for creating the first process instruction accesses a first set of empirical data, and the second method for creating the second process instruction accesses a second set of empirical data, wherein the first set of empirical data is different from the second set of empirical data. A method (400) for providing a process instruction for the additive manufacturing (M) of a component according to claim 27, characterized in that the first set of empirical data is stored on a first storage device and the second set of empirical data is stored on a second storage device, wherein the first storage device is different from the second storage device.Method (400) for providing a process instruction for the additive manufacturing (M) of a component according to one or more of the preceding claims, characterized in that the additive manufacturing (M) of a component comprises CAM methods, wherein CAM methods comprise laser and / or electron beam powder bed fusion, direct energy deposition (DED), binder jetting and / or other non-abrasive computer-aided manufacturing methods that are based on a tool path with process parameters assigned thereto.

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