Additive manufacturing process with optimization of a process plan

Abstract

Additive manufacturing process for producing a workpiece that exhibits: Adding a material in multiple layers to form a unit section of the workpiece, wherein the workpiece has multiple unit sections, each corresponding to multiple voxels of a digital representation of the workpiece; where the addition of each layer of the workpiece during a period of time exhibits: Predictions of an expected temperature change of the layer to be manufactured during the period, based on a process plan and a prediction model, wherein the prediction model is set up to predict a temperature change of at least one section of the workpiece; If the expected temperature change of the layer does not meet a predetermined condition, adjust the process plan to cause the expected temperature change to meet the predetermined condition, and produce the layer according to the adjusted process plan, wherein the adjusted process plan includes a scan path of a print head, a scan speed plan of the print head, a power supply plan of a power source, or a combination thereof; If the expected temperature change of the layer meets the specified condition, produce the layer according to the process plan; After the unit section of the workpiece has been formed, calibrate the prediction model, whereby the calibration exhibits: Capturing a real-time temperature of the unit section of the workpiece at a given time; Obtaining an expected temperature of the unit section at the given time based at least in part on the forecast model and the process plan; and Calibrating the forecast model based on the real-time temperature and the expected temperature; and After calibrating the prediction model, the material is added in multiple layers to form the next unit section of the workpiece using the calibrated prediction model.

Description

TECHNICAL AREA

[0001] Embodiments of the present invention relate to an additive manufacturing process with an optimization for a process plan. TECHNICAL AREA

[0002] In additive manufacturing and machining processes, temperature control of a workpiece is one of the most critical aspects. If a workpiece overheats during a manufacturing process, it can consequently suffer problems such as cracking, deformation, and an uneven crystal structure. In even more serious cases, overheating of the workpiece can even force the entire manufacturing process to be halted.

[0003] In the current state of the art, a process plan is usually created based on only one geometric parameter of a workpiece. If such a process plan is implemented, it can likely lead to a phenomenon where a specific section of the workpiece overheats during a manufacturing process, and it is difficult to effectively control the workpiece temperature.

[0004] Furthermore, in current technology, once a process plan is fully created in an additive manufacturing process, it is impossible to quickly change and adapt the process plan. Consequently, it is difficult to improve the manufacturing yield.

[0005] It is therefore necessary to create a new additive manufacturing process in order to solve at least one of the aforementioned problems.

[0006] WO 2017 / 131 613 A1, EP 3 208 077 A1, WO 2008 / 104 213 A1 and WO 2016 / 193 742 A1 each disclose an additive manufacturing process for producing a workpiece comprising the following steps: adding a material in several layers to form the workpiece; predicting an expected temperature change of the layer to be produced during the period based on a process plan and a predictive model; if the expected temperature change of the layer does not meet a predetermined condition, adjusting the process plan to cause the expected temperature change to meet the predetermined condition and producing the layer according to the adjusted process plan; and if the expected temperature change of the layer does meet the predetermined condition, producing the layer according to the process plan.

[0007] WO 2016 / 195 665 A1 discloses an additive manufacturing process for layer-by-layer 3D printing of a target object, wherein sacrificial objects, which are not part of the target object, are placed at strategic locations on the build bed to improve temperature uniformity within the printing environment and to prevent physical distortion of the target object during manufacturing. The strategic locations are identified based on a target object model geometry and a determined temperature of the target region on the build bed. A temperature level in the target region is determined by calculating a predicted temperature at the location on the build bed using a thermal model and the target object model. Actual temperature data can be recorded and used to verify the accuracy of the determined temperature level.A specific location for a sacrificial object is identified where the determined temperature level of the target region is insufficient to reach a specific temperature threshold for manufacturing.

[0008] FR 3 029 829 A1 describes a method for characterizing a given powder material for use in an additive manufacturing process. Several numerical simulations are run based on a digital simulation model with different thermal conductivity values ​​of powders, and the numerical results are compared with actual experimental test results. Once a numerical simulation has been identified that closely approximates the actual experiment, it is determined that the thermal conductivity value of the powder used for this simulation is a satisfactory estimate of the actual thermal conductivity of the given powder material. BRIEF DESCRIPTION OF THE INVENTION

[0009] According to the present invention, an additive manufacturing process for producing a workpiece is provided. The process comprises: adding a material in multiple layers to form a unit section of the workpiece. The workpiece has multiple unit sections, each corresponding to multiple voxels of a digital representation of the workpiece. One step of adding each layer of the workpiece during a period of time comprises: predicting an expected temperature change of the layer to be produced during the period of time based on a process plan and a predictive model, wherein the predictive model is configured to predict a temperature change of at least one section of the workpiece;If the expected temperature change of the layer does not meet a predetermined condition, the process plan is adjusted to cause the expected temperature change to meet the predetermined condition, and the layer is produced according to the adjusted process plan, wherein the adjusted process plan includes a scan path of a printhead, a scan rate plan of the printhead, a power supply plan of a power source, or a combination thereof; and if the expected temperature change of the layer meets the predetermined condition, the layer is produced according to the process plan. The method further includes, after the unit section of the workpiece has been formed, calibrating the prediction model, wherein the calibration comprises: acquiring a real-time temperature of the unit section of the workpiece at a given time;Obtaining an expected temperature of the unit section at the given time based at least in part on the prediction model and the process plan; and calibrating the prediction model based on the real-time temperature and the expected temperature. The method further includes, after calibrating the prediction model, adding the material in multiple layers to form the next unit section of the workpiece using the calibrated prediction model.

[0010] In the aforementioned additive manufacturing process, predicting the expected temperature change of the layer may further include predicting a maximum temperature and a minimum temperature for each unit section in the layer during the given period, and adjusting the process plan may further include adjusting the process plan in response to either the maximum temperature or the minimum temperature being outside a specified temperature range.

[0011] Any of the aforementioned additive manufacturing processes can furthermore involve building the prediction model based on a boundary condition, a geometric parameter of the workpiece, and a property of the workpiece material.

[0012] Any of the aforementioned additive manufacturing processes may also involve creating the process plan before adding the material.

[0013] The scan speed plan can include a temporal scan speed change of the print head, a spatial scan speed change of the print head, or a combination of these.

[0014] Additionally or as an alternative, the energy supply plan can show a temporal change in the power output of the energy source, a spatial change in the power output of the energy source, or a combination of these. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] These and other features, aspects and advantages of the present invention will become clearer when the following detailed description has been read with reference to the accompanying drawings, in which the same reference numerals denote the same parts throughout the drawings, wherein they show: Fig. 1 a flowchart of a method for optimizing an additive manufacturing process plan according to an embodiment which is not claimed as such; Fig. 2 a flowchart of a method for optimizing an additive manufacturing process plan according to a further embodiment, which is not claimed as such; Fig. 3 a flowchart of an additive manufacturing process according to a particular embodiment of the present invention; and Fig. 4 A schematic representation of an optimizer for optimizing an additive manufacturing process plan according to an embodiment which is not claimed as such. DETAILED DESCRIPTION OF EXECUTION FORMS

[0016] The specific implementations of the present invention are described in detail below with reference to the accompanying drawings, in order to enable those skilled in the field to fully understand the subject matter claimed by the present invention. In the following detailed description of these specific embodiments, the present disclosure does not describe in detail every known function or configuration in order to avoid unnecessary details that could impair the disclosure of the present invention.

[0017] Unless otherwise defined, the technical and scientific terms used in the claims and the description are as they are normally understood by those skilled in the art in the field to which the present invention belongs. "First," "second," and similar words used in the description and the claims do not denote any order, quantity, or importance, but are merely intended to distinguish between different components. The expressions "a single," "a," and similar words are not intended to be limiting, but rather denote the presence of at least one."Exhibit," "consist of," and similar words mean that the elements or objects appearing before "exhibit" or "consist of" include the elements or objects and their equivalent elements appearing after "exhibit" or "consist of," without excluding any other elements or objects. "Connected," "coupled," and similar words are not limited to physical or mechanical connections but may also include electrical connections, either direct or indirect.

[0018] The methods in the embodiments of the present invention are illustrated in the figures as functional modules. It should be mentioned that a sequence of modules and a division of actions within the modules, as shown in the figures, are possible. Fig. 1 to Fig. The possibilities illustrated in Figure 3 are not limited to the embodiments shown in the figures. For example, modules can be executed in different sequences, and an action in one module can be an action in combination with another module or several modules, or it can be divided among several modules.

[0019] The embodiments of the present invention relate to a process plan optimization method that is applicable in a variety of ways to additive manufacturing process procedures and is able to optimize a process plan for additive manufacturing in order to improve the quality and performance of a finished product.

[0020] Fig. Figure 1 shows a flowchart of a method 100 for optimizing a process plan for additive manufacturing according to an embodiment which is not claimed as such, but is part of the process described in Figure 100. Fig. Figure 3 illustrates an additive manufacturing process. The process plan is an additive manufacturing process plan, and in the process plan, a workpiece to be manufactured is produced or formed by adding material in multiple layers. In some embodiments, a non-optimized process plan includes the power of an energy source and a scan path of a print head, and it is created according to a geometric parameter of a workpiece.

[0021] Referring to Fig. 1. The procedure 100 includes a modeling step 110, a prediction step 120, a determination step 130 and an adjustment step 140.

[0022] First, as illustrated in step 110, a predictive model is constructed, which can be configured to predict a temperature change of at least one section of the workpiece. The "temperature change" referred to herein includes a change in the temperature of a section of the workpiece to be detected over a period of time. In some embodiments, the predictive model can be constructed based on a geometric parameter of the workpiece, a boundary condition, and a property of the workpiece material. The "geometric parameter" mentioned herein includes a target size, shape, or the like of the workpiece to be manufactured. The "boundary condition" refers to a sum of effects on the temperature of the workpiece exerted by elements or substances surrounding the workpiece that are capable of exchanging heat with it.The “property of the material” includes a chemical property of the material, a physical property of the material, or a combination of these, where the physical property includes a grain size of the material and the like.

[0023] In step 120, the expected temperature change of the workpiece section to be manufactured during a given period is predicted based on the predictive model and the process plan. In some embodiments, the given period can range from approximately 5 seconds to 60 seconds. For example, the given period is approximately 10 seconds. In some embodiments, the workpiece section to be manufactured is a section within a specific layer, a specific layer, or several layers of the material. The expected temperature change includes a temperature distribution of the workpiece section at each point in time within the given period.

[0024] Subsequently, as illustrated in step 130, the expected temperature change of the section is compared with a predefined condition to determine whether the expected temperature change of the section meets the predefined condition.

[0025] If the expected temperature change of the section does not meet the specified condition, step 140 is performed; that is, the process plan is adjusted to cause the expected temperature change of the section to meet the specified condition. The adjusted process plan may include a printhead scan path, a printhead scan speed plan, a power supply plan for a power source, or a combination thereof. The scan speed plan includes a temporal scan speed change of the printhead, a spatial scan speed change of the printhead, or a combination thereof.

[0026] In some embodiments, the workpiece contains multiple unit sections, each corresponding to several voxels of a digital representation of the workpiece. The prediction step includes predicting an expected temperature change range for each unit section to be manufactured during the given time period; then comparing the expected temperature change range of each unit section with a predetermined temperature range; and if the expected temperature change range does not fall within the predetermined temperature range, adjusting the process plan to cause the expected temperature change range to fall within the predetermined temperature range.In particular, the prediction step includes predicting a maximum and a minimum temperature for each unit section to be manufactured during the given period, and adjusting the process plan accordingly, and adjusting the process plan accordingly if either the maximum or the minimum temperature is outside a predetermined temperature range. In some embodiments, the multiple unit sections in the workpiece may correspond to the same predetermined temperature range. In other embodiments, the multiple unit sections in the workpiece may each correspond to different predetermined temperature ranges.

[0027] Because it is unavoidable that an error exists in a prediction model built on the basis of a boundary condition, a geometric parameter of the workpiece, and a property of the workpiece material, some embodiments further include a calibration step of the prediction model to improve its accuracy. Referring to Fig. 2 contains a method 300, which is not claimed as such, but is part of the one in Fig. The additive manufacturing process shown in Figure 3 comprises a modeling step 310, calibration steps 320 to 340, a prediction step 350, a determination step 360 and an adjustment step 370.

[0028] Similar to step 110, in step 310 a prediction model is built based on a geometric parameter of a workpiece, a boundary condition and a property of the material of a workpiece.

[0029] In step 320, a real-time temperature of a given unit section of the workpiece at a given time is acquired as a basis for calibration. In step 330, an expected temperature of the given unit section at the given time is obtained based at least partially on the prediction model and the process plan, which are not calibrated.

[0030] The prediction model is then calibrated based on the recorded real-time temperature of the unit section and the calculated expected temperature of the unit section, as illustrated in step 340. Specifically, the calibration step involves calibrating either a property of the material and / or a boundary condition of the workpiece.

[0031] Steps 350-370 are similar to steps 120-140, which are described in Fig. Figure 1 illustrates this. Details are not described again here.

[0032] It should be noted that the calibration step does not have to precede the prediction step and the calibration step can be placed at any other suitable point in the procedure 300.

[0033] Another aspect of this application relates to an additive manufacturing process for producing a workpiece, which includes: adding a material in several layers to form the workpiece until the workpiece is fully manufactured, wherein the step of adding each layer of the workpiece during a period of time includes: predicting an expected temperature change of the layer to be manufactured during the period of time, based on a process plan and a predictive model of the layer; if the expected temperature change of the layer does not meet a predetermined condition, adjusting the process plan to cause the expected temperature change to meet the predetermined condition, and subsequently manufacturing the layer according to the adjusted process plan; and if the expected temperature change of the layer meets the predetermined condition, manufacturing the layer according to the process plan.

[0034] Referring to Fig. 3 contains an additive manufacturing process 500, including a process planning step 510, a prediction model setup step 520, steps 531-534 of manufacturing a first layer, and steps 541-544 of manufacturing a second layer.

[0035] In particular, step 510 creates an initial process plan for manufacturing the workpiece. Generally speaking, the process plan can be created based on a defined geometric parameter of the workpiece and / or material used to manufacture the workpiece, and process plan parameters can include the power output of a power source and the scan path of a print head. In step 520, the predictive model is built based on a geometric parameter of the workpiece, a boundary condition, and a property of the workpiece material. Similar to steps 110 and 310, the predictive model can be configured to predict a temperature change in at least one section of the workpiece. Specifically, the temperature change refers to a change in the temperature distribution of the workpiece section over time that is to be predicted.

[0036] The material is then added layer by layer until the workpiece is completely finished.

[0037] Specifically, in step 531, an expected temperature change of the first layer to be produced is predicted based on the process plan and the predictive model obtained in steps 510 and 520. The expected temperature change of the first layer encompasses the temperature change of the first layer of the workpiece over time within a period during the production of the first layer. Subsequently, as illustrated in step 532, the expected temperature change of the first layer is compared to a predefined condition to determine whether the expected temperature change of the first layer meets the predefined condition.

[0038] If the expected temperature change of the first layer meets the specified condition, it is indicated that the first layer, manufactured according to the current process plan, can meet the requirements. Consequently, in this case, the first layer is added immediately according to the initial process plan, as illustrated in step 533.

[0039] If the expected temperature change of the first layer does not meet a predefined condition, step 534 is performed to adjust the process plan to make the expected temperature change of the first layer meet the predefined condition. Step 531 is then performed again to predict the expected temperature change of the first layer again based on the prediction model and the adjusted process plan. Step 532 is then performed again to determine whether the expected temperature change meets the predefined condition, and if the expected temperature change still does not meet the predefined condition, step 534 is performed again to adjust the process plan once more.Steps 531, 532 and 534 can be repeated until the expected temperature change of the first layer meets the specified condition, and then the first layer is manufactured according to the optimized process plan to ensure that the first layer would not overheat during the first layer manufacturing process.

[0040] Steps 541-544 are steps for predicting, determining, and manufacturing a second layer of the workpiece, where steps 541-544 are similar to steps 531-534 and details are not repeated. The second layer can be an adjacent layer to the first layer, a layer added immediately above the first layer, or a layer not adjacent to the first layer.

[0041] Assuming the workpiece contains N layers, the workpiece is formed by adding material in N layers. Similarly, the process may further include steps for manufacturing a third layer, steps for manufacturing a fourth layer, ..., and steps for manufacturing an Nth layer, all manufacturing steps being similar to the preceding steps for manufacturing the first or second layer. Before each layer is added, a temperature change of the layer is predicted, and subsequently, the process plan is adjusted as necessary.In light of the foregoing, according to the disclosure of the present invention, in contrast to an existing additive manufacturing process, an additive manufacturing process plan can be flexibly adapted and optimized in real time according to the real-time status of a process procedure, so that a temperature distribution of the workpiece in a manufacturing process can be effective, thereby avoiding a phenomenon of local overheating and helping to increase the yield of the manufacturing and improve the quality of a finished product.

[0042] This application also concerns a process plan optimizer for optimizing an additive manufacturing process plan.

[0043] Fig. Figure 4 shows a schematic representation of a process plan optimizer 700 for additive manufacturing, which is not claimed as such, according to one embodiment. Referring to Fig.4. The optimizer 700 contains a modeler 710, a predictor 750, an optimization comparator 760 and a corrector 770.

[0044] The modeler 710 is configured to build a prediction model 810, wherein the prediction model 810 is configured to predict a temperature change of at least one section of the workpiece.

[0045] The predictor 750 is set up to predict an expected temperature change 830 of the section of the workpiece to be manufactured during a given period of time, based on the prediction model 810 and the process plan 870.

[0046] The optimization comparator 760 is set up to compare the expected temperature change of section 830 with a given condition 880 to determine whether the expected temperature change of section 830 satisfies the given condition 880.

[0047] The corrector 770 is configured to adjust the process plan in response to the fact that the expected temperature change of the section does not meet a predetermined condition, in order to cause the expected temperature change of the section to meet the predetermined condition. In particular, in some embodiments, when the optimization comparator 760 determines that the expected temperature change 830 does not meet the predetermined condition 880, a correction signal 840 is sent to the corrector 770, and after receiving the correction signal 840, the corrector 770 adjusts the process plan.

[0048] The optimizer 700 further includes a calibration device configured to calibrate the prediction model. The calibration device comprises a computer 720, a detector 730, and a calibrator 740. The computer 720 is configured to obtain an expected temperature 850 of the given unit section at the given time based at least in part on the prediction model 810 and the process plan, wherein the unit section corresponds to a voxel in a digital representation of the workpiece. The detector 730 is configured to detect a real-time temperature 860 of the given unit section of the workpiece at a given time. In some embodiments, the detector 730 is provided on a platform for supporting the workpiece and vertical walls surrounding the workpiece, or a combination thereof.The calibrator 740 is configured to calibrate the prediction model 810 based on the real-time temperature 860 and the expected temperature 850 to obtain a calibrated prediction model 820. Subsequently, the predictor 750 predicts the expected temperature change 830 of the section of the workpiece to be manufactured during a given period, based on the calibrated prediction model 820 and the process plan 870.

[0049] In some embodiments, the calibration device further includes a (not illustrated) calibration comparator configured to compare the real-time temperature 860 with the expected temperature 850 to obtain a difference between them, and the calibrator 740 calibrates the prediction model 810 on the basis of the difference.

[0050] While the present invention has been described in detail with reference to its specific embodiments, it will be clear to those skilled in the field that many modifications and alterations can be made to the present invention. It is therefore to be understood that the appended claims are intended to encompass all such modifications and alterations, provided they are within the true scope and extent of the invention.

Claims

[1] Additive manufacturing process for producing a workpiece which has: Adding a material in multiple layers to form a unit section of the workpiece, wherein the workpiece has multiple unit sections, each corresponding to multiple voxels of a digital representation of the workpiece; where the addition of each layer of the workpiece during a period of time exhibits: Predictions of an expected temperature change of the layer to be manufactured during the period, based on a process plan and a prediction model, wherein the prediction model is set up to predict a temperature change of at least one section of the workpiece; If the expected temperature change of the layer does not meet a predetermined condition, adjust the process plan to cause the expected temperature change to meet the predetermined condition, and produce the layer according to the adjusted process plan, wherein the adjusted process plan includes a scan path of a print head, a scan speed plan of the print head, a power supply plan of a power source, or a combination thereof; If the expected temperature change of the layer meets the specified condition, produce the layer according to the process plan; After the unit section of the workpiece has been formed, calibrate the prediction model, whereby the calibration exhibits: Capturing a real-time temperature of the unit section of the workpiece at a given time; Obtaining an expected temperature of the unit section at the given time based at least in part on the forecast model and the process plan; and Calibrating the forecast model based on the real-time temperature and the expected temperature; and After calibrating the prediction model, the material is added in multiple layers to form the next unit section of the workpiece using the calibrated prediction model. [2] Additive manufacturing process according to claim 1, wherein the prediction of the expected temperature change of the section further comprises a prediction of a maximum temperature and a minimum temperature for each unit section to be manufactured during the given period, and the adjustment of the process plan further comprises an adjustment of the process plan in response to either the maximum temperature or the minimum temperature being outside a predetermined temperature range. [3] Additive manufacturing process according to claim 1 or 2, further comprising building the prediction model on the basis of a boundary condition, a geometric parameter of the workpiece and a property of the material of the workpiece. [4] Additive manufacturing process according to any one of the preceding claims, wherein the calibration of the prediction model further comprises a calibration of either a property of the material and / or a boundary condition of the workpiece. [5] Additive manufacturing process according to claim 1, wherein the scan speed plan comprises a temporal scan speed change of the print head, a spatial scan speed change of the print head or a combination thereof. [6] Additive manufacturing process according to claim 1, wherein the energy supply plan includes a temporal power change of the energy source, a spatial power change of the energy source or a combination of these.

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