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WO2022054144A1 - Procédé d'évaluation de lit de poudre dans la mise en forme de stratifié, système de mise en forme de stratifié, dispositif de traitement d'informations, et procédé de commande et programme de commande associé - Google Patents

Procédé d'évaluation de lit de poudre dans la mise en forme de stratifié, système de mise en forme de stratifié, dispositif de traitement d'informations, et procédé de commande et programme de commande associé Download PDF

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Publication number
WO2022054144A1
WO2022054144A1 PCT/JP2020/034005 JP2020034005W WO2022054144A1 WO 2022054144 A1 WO2022054144 A1 WO 2022054144A1 JP 2020034005 W JP2020034005 W JP 2020034005W WO 2022054144 A1 WO2022054144 A1 WO 2022054144A1
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WIPO (PCT)
Prior art keywords
powder bed
powder
modeling
information processing
surface texture
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Ceased
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PCT/JP2020/034005
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English (en)
Japanese (ja)
Inventor
牧子 家田
秀樹 京極
敏孝 池庄司
将治 田上
孝樹 竹下
洋 青木
千佳 加藤
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Technology Research Association for Future Additive Manufacturing (TRAFAM)
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Technology Research Association for Future Additive Manufacturing (TRAFAM)
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Priority to PCT/JP2020/034005 priority Critical patent/WO2022054144A1/fr
Priority to JP2022548278A priority patent/JPWO2022054144A1/ja
Publication of WO2022054144A1 publication Critical patent/WO2022054144A1/fr
Anticipated expiration legal-status Critical
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F3/00—Manufacture of workpieces or articles from metallic powder characterised by the manner of compacting or sintering; Apparatus specially adapted therefor ; Presses and furnaces
    • B22F3/12—Both compacting and sintering
    • B22F3/16—Both compacting and sintering in successive or repeated steps
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y50/00—Data acquisition or data processing for additive manufacturing
    • B33Y50/02—Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes

Definitions

  • the present invention relates to a powder bed evaluation method in laminated modeling, a laminated modeling system, an information processing apparatus, and a control method and control program thereof.
  • Patent Document 1 discloses a technique of photographing the surface texture of a material layer with a digital camera, evaluating the flatness of the surface, and changing the moving speed and pressure of a blade for skiing a powder material. ing. Then, it is described that the energy density and the temperature distribution at the time of laser irradiation are affected by the change of the moving speed and the pressure of the blade (see paragraphs [0081] and [0141]). Further, in Non-Patent Document 1, a dedicated recoating device is developed and the powder characteristics, powder supply amount, recoating speed, and speed change of powder Avalanche angle are analyzed by ANOVA, and the spreadability of the powder is analyzed. We are considering the impact on. Further, in Non-Patent Document 2, the powder characteristics of the Ti-6Al-4V powder and the surface texture of the powder bed are photographed with a digital camera and evaluated qualitatively.
  • An object of the present invention is to provide a technique for solving the above-mentioned problems.
  • the information processing apparatus is It is an information processing device that controls a laminated modeling device that produces a model by irradiating a laser on a powder bed covered with material powder.
  • the first data acquisition unit that acquires the three-dimensional point cloud data of the powder bed surface before laser irradiation, and A first parameter calculation unit that calculates surface texture parameters obtained by reducing the three-dimensional point cloud data of the powder bed surface to a lower dimension.
  • a control unit that evaluates the state of the powder bed surface using the surface texture parameters of the powder bed surface and controls the production of the modeled object by the laminated modeling device. To prepare for.
  • the control method of the information processing apparatus is It is a control method of an information processing device that controls a laminated modeling device that manufactures a model by irradiating a powder bed on which material powder is spread with a laser.
  • the control program of the information processing apparatus is It is a control program of an information processing device that controls a laminated modeling device that manufactures a model by irradiating a laser on a powder bed covered with material powder.
  • a control step that evaluates the state of the powder bed surface using the surface texture parameters of the powder bed surface and controls the production of the modeled object by the laminated modeling device. Let the computer run.
  • the laminated modeling system A laminated modeling device that produces a model by irradiating a laser on a powder bed covered with material powder,
  • An information processing device that controls the production of the modeled object in the laminated modeling device, Equipped with The information processing device is The first data acquisition unit that acquires the three-dimensional point cloud data of the powder bed surface before laser irradiation, and A first parameter calculation unit that calculates surface texture parameters obtained by reducing the three-dimensional point cloud data of the powder bed surface to a lower dimension.
  • a control unit that evaluates the state of the powder bed surface using the surface texture parameters of the powder bed surface and controls the production of the modeled object by the laminated modeling device. To prepare for.
  • the method according to the present invention It is a powder bed evaluation method in laminated modeling that irradiates a laser on a powder bed covered with material powder to produce a model.
  • the evaluation result of the surface texture of the bower bed can be reflected in the improvement of the molding quality.
  • PB powder bed
  • the information processing apparatus 100 as the first embodiment of the present invention will be described with reference to FIG.
  • the information processing device 100 is a device that controls a laminated modeling device 110 that produces a modeled object by irradiating a powder bed on which material powder is spread with a laser.
  • the information processing apparatus 100 includes a data acquisition unit 101, a parameter calculation unit 102, and a control unit 103.
  • the data acquisition unit 101 acquires three-dimensional point cloud data on the surface of the powder bed before laser irradiation.
  • the parameter calculation unit 102 calculates the surface texture parameter obtained by reducing the three-dimensional point cloud data of the powder bed surface to a lower dimension.
  • the control unit 103 evaluates the state of the powder bed surface using the surface texture parameter of the powder bed surface, and controls the production of the modeled object by the laminated modeling device 110.
  • the evaluation result of the surface texture of the bower bed can be reflected in the improvement of the molding quality.
  • the information processing apparatus that controls the laminated modeling system according to the second embodiment of the present invention will be described.
  • the three-dimensional point cloud data of the powder bed surface is acquired, the surface texture parameter obtained by reducing the three-dimensional point cloud data to a lower dimension is calculated, and the state of the powder bed surface is evaluated using the surface texture parameter.
  • the surface texture parameter of the present embodiment includes at least one of Sq (Root mean square height of the surface), Sv (Maximum height of valleys) and Sp (Maxmum height of peaks).
  • the degree of unevenness on the surface of the powder bed is evaluated using the surface texture parameter, and the continuation or discontinuation of the production of the modeled object by the laminated modeling device is instructed.
  • the thickness of the layer of the powder bed is evaluated using the surface texture parameter, and the moving speed of the recorder that produces the powder bed and the recycling amount of the powder material used for producing the powder bed are instructed to be adjusted.
  • the surface texture parameters refer to ISO 25178-2: 2012 of Non-Patent Document 3.
  • FIG. 2A is a diagram illustrating a laminated modeling technique according to the present embodiment.
  • the laminated modeling technology 200 in order to laminate and model a high-precision and high-quality modeled object, a technology 201 for generating design data and modeling condition data and an advanced monitoring / feedback control technology 202 have been researched and developed.
  • the surface texture observation 203 includes observing the properties of the powder bed surface and observing the properties of the modeling surface. Further, the elucidation 205 of the dissolution and solidification phenomenon includes observation of melt pool temperature and morphology and observation of sputtering.
  • the advanced monitoring / feedback control technology 202 includes, for example, a process 221 with defect prediction and a process 222 with actual defect detection based on machine learning of observation results or elucidation results.
  • the calculation of the surface texture parameter according to the present embodiment is a technique related to the surface texture observation 203 of the powder bed. Then, the surface texture observation 203 of the powder bed statically feeds back to the generation technology 201 of the design data and the modeling condition data, and contributes to the improvement thereof. Further, in the present embodiment, the defect prediction by the surface texture observation 203 of the powder bed can be linked to the real-time automatic conversion of the optimum conditions at the time of laminated molding.
  • FIG. 2B is a diagram illustrating an outline of operation of the information processing apparatus according to the present embodiment.
  • step S201 recoating with a blade is performed.
  • step S203 the surface of the powder bed is imaged and three-dimensional point cloud data is obtained.
  • step S205 a planar property parameter (2 ⁇ or the like) is calculated from the three-dimensional point cloud data, and the state of the powder bed surface is evaluated.
  • step S207 the unevenness of the powder bed surface may be displayed on a color map.
  • FIG. 3A is a block diagram showing the configuration of the laminated modeling system 310 according to the second embodiment.
  • the laminated modeling system 310 includes an information processing device 320 and a laminated modeling device 330.
  • the information processing device 320 may be mounted in the laminated modeling device 330 and realized as one device. Alternatively, the information processing device 320 may be divided into a plurality of processing functions and realized as a plurality of devices.
  • the laminated modeling device 330 includes a laser irradiation unit 311 that oscillates while scanning a laser that melts the material powder spread on the modeling surface and solidifies the modeled object, and a camera 312 that captures the powder bed surface and the modeling surface. .. Further, the laminated modeling apparatus 330 includes a modeling table 313 on which a modeled object is laminated and modeled, and powder laminating mechanisms 314 and 315 for spreading material powder on the modeling surface. In the laminated modeling device 330 of FIG. 3A, a part related to control by the information processing device 320 in the present embodiment will be described, and other description will be omitted.
  • the information processing device 320 controls the modeling of the laminated modeled object in the laminated modeling device 330.
  • the information processing apparatus 320 acquires image data of the powder bed surface and the modeling surface imaged by the camera 312 during the laminated modeling, and generates three-dimensional point cloud data.
  • the information processing apparatus 320 calculates at least one surface texture parameter whose modeling can be controlled based on the three-dimensional point cloud data within the modeling range.
  • the information processing apparatus 320 controls the generation of the powder bed surface and the laser output for modeling from the correlation between the surface texture parameters learned in advance and the molding quality by using the calculated surface texture parameters. ..
  • the three-dimensional point cloud data may be optionally calculated by the point cloud data calculation device 340 and acquired by the information processing device 320. Further, in order to shorten the calculation time, the surface texture parameters may be calculated at high speed outside the information processing apparatus 320. Further, the control of the modeling table 313 in which the modeled object is laminated is also affected by the modeling quality, but basically it is often set in advance as design data or modeling condition data, so the control thereof is omitted. For example, the thickness of one layer and the density of the spread material powder may be controlled.
  • FIG. 3B is a flowchart showing an operation procedure of the laminated modeling system 310 according to the present embodiment.
  • the modeling table (base plate) 313 is lowered by one layer in step S301.
  • one layer of material powder is skied in step S303.
  • the evaluation process of the powder bed is executed in step S305.
  • the laminated modeling system 310 proceeds from steps S307 to S309 to irradiate the laser irradiation corresponding to the model to be laminated. conduct.
  • step S311 it is determined whether or not there is data for the next layer, and if so, the formation of the next layer is repeated from step S301.
  • step S313 the modeling is stopped.
  • FIG. 4A is a block diagram showing a configuration of an information processing apparatus 320 that controls the laminated modeling system 310 according to the present embodiment.
  • the information processing apparatus 320 includes a communication control unit 401, an image pickup control unit 402, a three-dimensional point cloud data acquisition unit 403, a database 404, a surface texture parameter calculation unit 405, a powder bed evaluation unit 406, and laminated modeling control. It is provided with an instruction unit 407 and a laminated modeling continuation / stop instruction unit 408.
  • the information processing apparatus 320 of FIG. 4A shows a functional configuration related to the present embodiment, and omits control functions related to other laminated modeling and other functions realized by a general-purpose computer. For example, it is also provided with a display unit for transmitting design data and modeling condition data, receiving a state of laminated modeling, a display unit for notifying the state of laminated modeling, an instruction unit for input instruction by an operator, and the like.
  • the communication control unit 401 controls communication with the laminated modeling device 330 by wire or wirelessly.
  • the image pickup control unit 402 controls the image pickup of the modeling surface and the powder bed surface by the camera 312.
  • the 3D point cloud data acquisition unit 403 acquires the 3D point cloud data extracted from the images of the modeling surface and the powder bed surface captured by the camera 312.
  • the 3D point cloud data may be acquired from an external device, or may be generated by the 3D point cloud data acquisition unit 403.
  • the three-dimensional point cloud data is stored in the three-dimensional point cloud data storage unit 441 of the database 404.
  • the database 404 has a three-dimensional point cloud data storage unit 441, a surface texture parameter calculation formula storage unit 442, and a powder bed evaluation table 443.
  • the 3D point cloud data storage unit 441 stores the 3D point cloud data from the 3D point cloud data acquisition unit 403. If the history of 3D point cloud data is used, it is stored with a time stamp.
  • the surface texture parameter calculation formula storage unit 442 stores the calculation algorithm with each surface texture parameter as an identifier.
  • the powder bed evaluation table 443 stores a table prepared in advance for evaluating the powder bed from the calculated values of the surface texture parameters.
  • the surface texture parameter calculation unit 405 calculates the surface texture parameter by the calculation formula stored in the surface texture parameter calculation formula storage unit 442 using the three-dimensional point cloud data stored in the three-dimensional point cloud data storage unit 441. ..
  • the powder bed evaluation unit 406 evaluates the powder bed from the surface texture parameters of the powder bed surface calculated by the surface texture parameter calculation unit 405 with reference to the powder bed evaluation table 443.
  • the laminated modeling control instruction unit 407 has a powder bed generation control table 471, and the powder bed generation control table 471 is used for the laminated modeling apparatus 330 based on the evaluation result of the powder bed by the powder bed evaluation unit 406. Give instructions for modeling control. That is, when it is determined that the quality of the powder bed surface is low or the molding quality is likely to deteriorate, control for improving the quality of the powder bed surface is instructed. In the case of this embodiment, the moving speed of the recoater and the amount of recycled powder are adjusted in order to improve the quality of the powder bed surface.
  • the laminated modeling continuation / cancellation instruction unit 408 has a modeling stop condition table 481, and when the quality of the powder bed surface and the modeling quality that satisfy the modeling stop condition of the modeling stop condition table 481 are evaluated, the laminated modeling is stopped. Instruct. If the conditions for discontinuing modeling are not met, laminated modeling is continued.
  • FIG. 4B is a diagram showing the configuration of the powder bed evaluation table 443 according to the present embodiment.
  • the powder bed evaluation table 443 is used by the powder bed evaluation unit 406 to evaluate the quality of the powder bed.
  • the powder bed evaluation table 443 stores the judgment threshold value 432 and the information 433 about the correlation with other parameters in association with the surface texture parameter 431.
  • the quality of the powder bed surface is evaluated by Sq (2 ⁇ ), Sv (Min), and Sp (Max) as the surface texture parameter 431 of the powder bed.
  • FIG. 4C is a flowchart showing a processing procedure of the information processing apparatus 320 according to the present embodiment.
  • the flowchart of FIG. 4C corresponds to S305 of FIG. 3B, and is executed by the CPU of the information processing apparatus 320 using RAM or the like to realize the components of FIG. 4A.
  • the information processing apparatus 320 acquires three-dimensional point cloud data on the surface of the powder bed in step S401.
  • the three-dimensional point cloud data may be acquired from the outside or calculated from the image data in the information processing apparatus 320.
  • the information processing apparatus 320 calculates the surface texture parameter from the three-dimensional point cloud data in step S403. In this embodiment, Sq (2 ⁇ ), Sv (Min), and Sp (Max) are calculated.
  • the information processing apparatus 320 determines in step S405 whether or not the calculated Sq (2 ⁇ ), Sv (Min), and Sp (Max) are equal to or less than the threshold value a (modeling quality can be guaranteed).
  • the threshold value a may be determined by any one of Sq (2 ⁇ ), Sv (Min), and Sp (Max), independently of each, or by a combination. If it is equal to or less than the threshold value a, it is OK, and the process proceeds to step S307 of FIG. 3B. If it is not equal to or less than the threshold value a, if the condition can be selected, the condition is selected, or if it is not OK, the process proceeds to step S307 of FIG. 3B.
  • the evaluation result of the surface texture of the bower bed can be reflected in the improvement of the molding quality.
  • the information processing apparatus acquires the three-dimensional point cloud data of the modeling surface and calculates the surface texture parameter obtained by lowering the three-dimensional point cloud data. different. Since other configurations and operations are the same as those in the second embodiment, the same configurations and operations are designated by the same reference numerals and detailed description thereof will be omitted.
  • the three-dimensional point cloud data of the modeling surface is acquired, the surface texture parameter obtained by reducing the three-dimensional point cloud data to a lower dimension is calculated, and the surface texture parameter of the modeling surface is calculated.
  • the state of the modeling surface is evaluated using the above, and the production of the modeled object by the laminated modeling device is controlled.
  • the state of the powder bed surface is evaluated using the surface texture parameter of the powder bed surface and the surface texture parameter of the modeling surface, and the production of the modeled object by the laminated modeling device is controlled.
  • FIG. 5 is a flowchart showing an operation procedure of the laminated modeling system according to the present embodiment.
  • the same step numbers as those in FIG. 3B are assigned the same step numbers, and duplicate explanations will be omitted.
  • step S509 the modeling surface after laser irradiation is imaged to evaluate the modeling quality. Then, in the laminated modeling system, in step S510, it is determined whether or not the modeling quality is OK. It should be noted that the modeling quality includes the layer formed and the prediction of the quality of the modeled object after modeling. If the modeling quality is OK, the process proceeds to step S311. If the modeling quality is not OK, for example, in step S313, modeling is stopped.
  • FIG. 6A is a block diagram showing a configuration of an information processing apparatus 620 that controls a laminated modeling system according to the present embodiment.
  • the same reference numbers are assigned to the same components as in FIG. 4A, and duplicate description will be omitted.
  • the information processing apparatus 620 includes a database 604, a modeling quality evaluation unit 606, a laminated modeling control instruction unit 607, and a laminated modeling continuation / stop instruction unit 608.
  • Database 604 further includes a modeling quality evaluation table 643.
  • the modeling quality evaluation unit 606 evaluates the modeling quality using the modeling quality evaluation table 643.
  • the laminated modeling control instruction unit 607 further has a process map 671 and instructs control such as laser intensity and scanning speed applied to modeling.
  • the laminated modeling continuation / stop instruction unit 608 has a modeling stop condition table 681 including a modeling stop condition based on the modeling quality, and instructs the continuation / cancellation of modeling based on the quality of the powder bed and the modeling quality.
  • FIG. 6B is a diagram showing the configuration of the modeling quality evaluation table 643 according to the present embodiment.
  • the modeling quality evaluation table 643 is used by the modeling quality evaluation unit 606 to predict the modeling density from the surface texture parameters and evaluate the modeling quality based on the predicted modeling density.
  • the modeling quality evaluation table 643 has a modeling density prediction table 650 for predicting the modeling density from three-dimensional surface texture parameters, and a modeling quality determination table 660 for determining the modeling quality based on the predicted modeling density.
  • the modeling density prediction table 610 has a correlation table 652 that maintains the correlation between the three-dimensional surface texture parameter and the relative density corresponding to the calculated three-dimensional surface texture parameter 651, and the correlation density predicted using the correlation table 652. 653 and are memorized.
  • the modeling quality determination table 660 stores the condition range 661 for determining the modeling quality based on the predicted relative density, and the modeling quality 622 of the determination result corresponding to each condition range 661.
  • ⁇ indicates high quality with a relative density of 99.7% or more
  • ⁇ indicates high quality with a relative density of less than 99.7% and 99.4% or more
  • ⁇ indicates a relative density of 99.4% or more. It represents good quality of less than 99.4% and 99.0% or more.
  • x represents low quality with relative density less than 99.0%.
  • it is not limited to the above conditions because the criteria for determining the modeling quality based on the relative density change depending on the application of the laminated model.
  • FIG. 6C is a flowchart showing a processing procedure of the information processing apparatus 620 according to the present embodiment. Note that FIG. 6C corresponds to S509 of FIG. 5, and is executed by the CPU of the information processing apparatus 620 using a RAM or the like to realize the components of FIG. 6A. Further, S305 in FIG. 5 is the same as in FIG. 4C.
  • the information processing apparatus 620 acquires the three-dimensional point cloud data of the modeling surface in step S601.
  • the three-dimensional point cloud data may be acquired from the outside or calculated from the image data in the information processing apparatus 620.
  • the information processing apparatus 620 calculates the surface texture parameter from the three-dimensional point cloud data in step S603. In this embodiment, Sal and the like are calculated.
  • the information processing apparatus 620 determines in step S605 whether or not the calculated Sal or the like is equal to or less than the threshold value b (the modeling quality can be guaranteed).
  • the threshold value a may be determined by any of Sal, independently of each other, or in combination. If it is equal to or less than the threshold value b, it is OK, and the process proceeds to step S510 in FIG. If it is not the threshold value b or less, if the condition can be selected, the condition is selected, or if it is not OK, the process proceeds to step S311 in FIG.
  • FIG. 6D is a flowchart showing another operation procedure of the laminated modeling system including the information processing apparatus 620 according to the present embodiment.
  • the same steps as in FIG. 3B are assigned the same step numbers, and duplicate description will be omitted.
  • step S610 the laminated modeling system combines the evaluation of the powder bed surface and the evaluation of the modeling surface to make a more accurate quality prediction of the modeled object. Then, in step S611, the laminated modeling system combines the evaluation of the powder bed surface and the evaluation of the modeling surface, and determines whether to continue or stop the modeling based on a more accurate quality prediction of the modeled object.
  • the evaluation result of the surface texture of the bower bed can be reflected in the improvement of the molding quality.
  • a powder suitable for the recoat system it is possible to select a powder suitable for the recoat system and determine specifications such as blades.
  • changes over time in powder quality can be determined and predicted in real time, recycled powder can be managed, and cost reduction can be achieved by minimizing powder waste.
  • the present inventors have found that the surface texture of the powder bed has a great influence on the quality such as the density, surface roughness and mechanical properties of the final product, but the powder characteristics, the recoating speed, and the shape of the blade of the recoater. It was recognized that the effects of the materials and materials on the surface properties of the powder bed have not been experimentally investigated.
  • An object of the present embodiment is to clarify the relationship between the powder property and the recoat behavior in PBF, quantify the obtained surface texture, and finally find the relationship with the quality of the modeled body. Therefore, in the present embodiment, first, a powder bed surface property measuring system including a powder recoating device and a layer surface measuring device capable of measuring the surface texture with high accuracy was designed and developed. Using this developed device, the surface texture of the powder bed was quantified, and the effects of the powder supply amount and recoat speed, which are the powder characteristics and recoat parameters, on the surface texture were investigated.
  • FIG. 7A is a diagram showing the configuration of a measurement system 700 for measuring the surface texture of the recoated powder material according to the present embodiment. Further, FIG. 7B is a diagram showing a method of acquiring a recoated material surface image according to the present embodiment.
  • the measurement system 700 used in this embodiment is composed of a recoat device (test bench) 713 for recoating powder and layer surface monitoring devices 711 and 712 for measuring surface texture.
  • the recoat device 713 is a device developed in the project and has a modeling section and a powder supply section as shown in 731 to 733.
  • the powder supply method is a method in which the powder is lifted from the supply section and supplied from below. There is.
  • the main specifications of the device are as follows. ⁇ Recoat speed: 30-40000 mm / min ⁇ Modeling area: 150 mm x 150 mm -Blade: Made of hard metal
  • the measurement principle is the pattern projection method. In this method, a two-dimensional pattern is projected onto an object by a laser projector 712, the image data is acquired by a light receiving camera 711 at another angle (see FIG. 7B), and the controller 714 is triangular from the amount of deformation of the two-dimensional pattern. This is a method of calculating three-dimensional shape (point group) data by the principle of surveying.
  • the process of quantifying the surface texture of the powder bed is shown below.
  • Surface texture is evaluated by using it as a variation in the height direction of unevenness on the surface.
  • a powder bed surface texture measuring system including a powder recoating device and a layer surface measuring device capable of measuring surface texture with high accuracy was designed and developed.
  • the surface texture of the powder bed was quantified, and the effects of the powder supply amount and recoat speed, which are the powder characteristics and recoat parameters, on the surface texture were investigated.
  • the results obtained are as follows. (1) We have developed a surface texture measuring device consisting of a powder recoating device and a layer surface measuring device that can measure the surface texture with high accuracy, and set the surface roughness 2 ⁇ to the entire surface of the powder bed with a height resolution of ⁇ 30 ⁇ m. It was confirmed that it could be measured.
  • the surface texture depends on the powder characteristics and the recoating speed, and the value of the surface roughness 2 ⁇ increases sharply at the recoating speed of 50 mm / s or more for all three types of powder.
  • the irregularly shaped powder has a coarser surface roughness than the other powders, and at a recoating speed of 15 mm / s to 50 mm / s, the surface roughness 2 ⁇ is 19 ⁇ m, and the other powders have a surface roughness of 17 ⁇ m.
  • the spherical powder showed the best surface roughness.
  • the surface texture of the bimodal powder was more susceptible to the recoat rate than the single peak powder. all right.
  • the surface roughness of the powder bed can be evaluated by the angle of repose or BFE.
  • the conditions are as follows. (The relative density of the 10mm Cube produced under the same conditions was 100.3%) ⁇ Round bar diameter: 12 mm ⁇ Modeling conditions: Laser, P (W) 300 : Scan speed, SS (mm / s) 1000 : Hatch distance, dy (mm) 0.10 : Layer thickness, dz (mm) 0.05 : Energy density, E (J / mm ⁇ 3) 60.0
  • the Sq (2 ⁇ ), Sv (Min), and Sp (Max) of the panda bed surface and the modeling surface from the 1298 layer (Layer) to the 1309 layer (Layer) were as shown in Table 1.
  • FIGS. 8A to 8C The graphs of Table 1 for each of Sq (2 ⁇ ), Sv (Min), and Sp (Max) with the layer as the horizontal axis are shown in FIGS. 8A to 8C.
  • the numbers on the graph indicate the order of laminated modeling (1 ⁇ 2 ⁇ 3 ⁇ ... ⁇ 23 ⁇ 24).
  • FIG. 8F shows other measurement results regarding the change in 2 ⁇ between the powder bed surface and the modeling surface.
  • "PB" in Table 1 and FIGS. 8A-8F represents a "powder bed surface”
  • “Melting (Ment)" represents a "modeled surface after laser irradiation”.
  • -Melting 16 or 18 1305th layer or 1306th layer may have voids. -There is a layer where spatter is likely to occur even under the same modeling conditions. This is thought to be due to the relationship between the laser scanning direction and the gas flow direction (SLM Solutions has a parameter that controls the laser scanning direction by deriving the gas flow direction).
  • an increase in 2 ⁇ means that the powder layer thickness changes, and the change in the powder layer thickness naturally affects the molding quality.
  • Min's index the correlation between the molten surface and the powder bed is relatively high, and it can be seen that scratches on the powder bed affect the quality of the shaped surface.
  • FIG. 9A SEM photographs are shown in FIG. 9A, and the particle size distribution of these powders is shown in FIG. 9B.
  • the powder A is a gas atomized powder having a wide particle size distribution and an irregular shape.
  • the B powder is a centrifugal atomized powder and is a spherical powder having a narrow particle size distribution.
  • the C powder is a gas atomized powder, which is a bimodal powder having a particle size distribution having two peaks of a fine powder and a coarse powder, and is a spherical powder with satellites.
  • the circularity is also shown, but the circularity of the B powder is the highest, and the C powder is lower than the B powder.
  • the powder supply method of the apparatus used in this embodiment is a commonly used rising method.
  • the powder supply amount was defined by the ratio of the rising value of the powder supply section divided by the falling value of the modeling section, and the surface texture was measured by changing to 1, 1.5, 2 and 3.
  • PSR powder supply amount
  • the powder supply amount was insufficient and a uniform powder bed could not be obtained, but when the PSR was "1.5” or more, a uniform powder bed could be obtained. .. Since there was no significant change in the surface texture of the powder bed at PSR "1.5” or higher, the result of the surface texture with respect to the recoat rate when the PSR is "2" is shown in FIG. 10A.
  • the A powder is a convex part, while the C powder is a concave part.
  • the surface texture of the A powder having poor fluidity deteriorates as the recoating speed increases.
  • the B powder has almost no change with respect to the change in the recoating rate, and the C powder is slightly affected.
  • FIG. 10 shows an image of the measured surface roughness change with respect to the recoating speed.
  • a powder many convex portions appear as the recoating speed increases, whereas in the B powder and the C powder, the change in the surface unevenness is small.
  • the A powder having poor fluidity is affected by the recoating speed, whereas the B powder and C powder having good fluidity are less affected by the recoating speed.
  • BFE also shows the same tendency as the angle of repose, which is considered to be an index for evaluating liquidity. Since BFE is also an index for observing cohesiveness, it is considered that the higher the BFE, the higher the value of 2 ⁇ . Since BFE has the same meaning as SE, it is considered to be an effective index for evaluating surface roughness.
  • the Carr index is an index that looks at the compressibility of the powder. As the index rises, 2 ⁇ decreases, and above 84, it is almost flat. This corresponds to B powder and C powder, and since these powders are excellent in compressibility, it is considered that the surface texture is also improved.
  • a surface texture measuring device consisting of a powder recoating device and a layer surface measuring device that can measure the surface texture with high accuracy, and set the surface roughness 2 ⁇ to the entire surface of the powder bed with a height resolution of ⁇ 30 ⁇ m. It was confirmed that it could be measured.
  • the surface texture depends on the powder characteristics and the recoating speed, and the value of the surface roughness 2 ⁇ increases sharply at the recoating speed of 50 mm / s or more for all three types of powder.
  • the irregularly shaped powder has a coarser surface roughness than the other powders, and at a recoating speed of 15 mm / s to 50 mm / s, the surface roughness 2 ⁇ is 19 ⁇ m, and the other powders have a surface roughness of 17 ⁇ m.
  • the spherical powder showed the best surface roughness.
  • the surface texture of the bimodal powder was more susceptible to the recoat rate than the single peak powder. all right. (4) It was found that the surface roughness of the powder bed can be evaluated by the angle of repose or BFE.
  • FIGS. 11A and 11B show SEM images of powder A and powder B when recycled powder is mixed. Further, FIGS. 11C and 11D show graphs showing the relationship between the material mixed with the recycled powder and the surface texture (2 ⁇ ).
  • the recoating speed has a large effect on 2 ⁇ .
  • a large 2 ⁇ means that the powder layer thickness changes, and the change in the powder layer thickness naturally affects the molding quality. It has been reported that the stacking thickness affects the porosity.
  • the molding quality is verified mainly on the unevenness of the surface of the powder bed, but the technical idea of the present invention is also applied to the determination of foreign matter when scratches or the like occur, and the same effect is obtained. .. It is also applied to the determination of the water content of the powder, which greatly affects the fluidity of the powder, and has the same effect. It is also applied to the determination of the influence on the surface texture due to the malfunction of the recoater, and has the same effect. Further, although the invention of the present application has been described with reference to the embodiments, the invention of the present application is not limited to the above-described embodiment. Various changes that can be understood by those skilled in the art can be made to the structure and details of the present invention within the technical scope of the present invention. Also included in the technical scope of the invention are systems or devices in any combination of the different features contained in each embodiment.
  • the present invention may be applied to a system composed of a plurality of devices, or may be applied to a single device. Further, the present invention is also applicable when an information processing program or a control program that realizes the functions of the embodiment is supplied to a system or an apparatus and executed by a built-in processor.
  • the technical scope of the present invention includes a program installed in the computer, a medium containing the program, a server for downloading the program, and a processor for executing the program. ..
  • at least a non-transitory computer readable medium containing a program for causing a computer to execute a processing step included in the above-described embodiment is included in the technical scope of the present invention.

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Abstract

L'invention concerne un dispositif de traitement d'informations destiné à refléter un résultat d'évaluation des propriétés de surface d'un lit de poudre pour l'amélioration de la qualité de mise en forme. Ce dispositif de traitement d'informations commande un dispositif de mise en forme de stratifié qui émet un laser sur un lit de poudre sur lequel une poudre de matériau a été étalée pour produire un article mis en forme, le dispositif de traitement d'informations étant doté d'une unité d'acquisition de données qui acquiert des données de groupe de points 3D sur la surface du lit de poudre avant l'exposition laser, une unité de calcul de paramètres qui calcule des paramètres de propriétés de surface dans lesquels les données de groupe de points 3D de la surface de lit de poudre ont été réduites en dimension, et une unité de commande qui évalue l'état de la surface de lit de poudre à l'aide des paramètres de propriétés de surface de la surface de lit de poudre et commande la production de l'article mis en forme par le dispositif de mise en forme de stratifié.
PCT/JP2020/034005 2020-09-08 2020-09-08 Procédé d'évaluation de lit de poudre dans la mise en forme de stratifié, système de mise en forme de stratifié, dispositif de traitement d'informations, et procédé de commande et programme de commande associé Ceased WO2022054144A1 (fr)

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CN115026310A (zh) * 2022-05-17 2022-09-09 西南交通大学 一种基于支持向量回归的slm增材制造铺粉孔隙率预测方法
EP4484033A3 (fr) * 2023-03-17 2025-01-29 Ricoh Company, Ltd. Appareil de fabrication d'objet tridimensionnel, procédé de fabrication d'objet tridimensionnel, dispositif de commande et dispositif de récupération

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JP2018003147A (ja) * 2016-07-08 2018-01-11 キヤノン株式会社 ３次元造形方法、および３次元造形物の製造装置
JP2019513577A (ja) * 2016-02-18 2019-05-30 ヴェロ・スリー・ディー・インコーポレイテッド 正確な３次元印刷
JP2019525856A (ja) * 2016-07-20 2019-09-12 ワッカー ケミー アクチエンゲゼルシャフトＷａｃｋｅｒ Ｃｈｅｍｉｅ ＡＧ ３ｄプリンタおよび対象物をプリントするための方法
WO2019239531A1 (fr) * 2018-06-13 2019-12-19 株式会社ニコン Dispositif de calcul, système de détection, dispositif de moulage, procédé de calcul, procédé de détection, procédé de moulage, programme de calcul, programme de détection et programme de moulage

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JP2019513577A (ja) * 2016-02-18 2019-05-30 ヴェロ・スリー・ディー・インコーポレイテッド 正確な３次元印刷
JP2018003147A (ja) * 2016-07-08 2018-01-11 キヤノン株式会社 ３次元造形方法、および３次元造形物の製造装置
JP2019525856A (ja) * 2016-07-20 2019-09-12 ワッカー ケミー アクチエンゲゼルシャフトＷａｃｋｅｒ Ｃｈｅｍｉｅ ＡＧ ３ｄプリンタおよび対象物をプリントするための方法
WO2019239531A1 (fr) * 2018-06-13 2019-12-19 株式会社ニコン Dispositif de calcul, système de détection, dispositif de moulage, procédé de calcul, procédé de détection, procédé de moulage, programme de calcul, programme de détection et programme de moulage

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115026310A (zh) * 2022-05-17 2022-09-09 西南交通大学 一种基于支持向量回归的slm增材制造铺粉孔隙率预测方法
EP4484033A3 (fr) * 2023-03-17 2025-01-29 Ricoh Company, Ltd. Appareil de fabrication d'objet tridimensionnel, procédé de fabrication d'objet tridimensionnel, dispositif de commande et dispositif de récupération

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