WO2024063150A1 - Procédé d'inspection de produit fabriqué de manière additive et procédé de fabrication de produit fabriqué de manière additive - Google Patents

Procédé d'inspection de produit fabriqué de manière additive et procédé de fabrication de produit fabriqué de manière additive Download PDF

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WO2024063150A1
WO2024063150A1 PCT/JP2023/034367 JP2023034367W WO2024063150A1 WO 2024063150 A1 WO2024063150 A1 WO 2024063150A1 JP 2023034367 W JP2023034367 W JP 2023034367W WO 2024063150 A1 WO2024063150 A1 WO 2024063150A1
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brightness
average value
evaluation
data
value
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PCT/JP2023/034367
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English (en)
Japanese (ja)
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晶 牛
孝介 桑原
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株式会社プロテリアル
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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
    • B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
    • B22F10/20—Direct sintering or melting
    • 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
    • B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
    • B22F10/80—Data acquisition or data processing
    • 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
    • B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
    • B22F10/80—Data acquisition or data processing
    • B22F10/85—Data acquisition or data processing for controlling or regulating additive manufacturing processes
    • 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
    • B33Y10/00—Processes of additive manufacturing
    • 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 an additive product inspection method and an additive product manufacturing method.
  • a heat source such as a laser beam or an electron beam is supplied to the raw material powder on a substrate to melt and solidify the raw material powder to form a solidified layer, and this process is repeated to obtain a three-dimensional additive product.
  • a heat source such as a laser beam or an electron beam is supplied to the raw material powder on a substrate to melt and solidify the raw material powder to form a solidified layer, and this process is repeated to obtain a three-dimensional additive product.
  • this additive manufacturing method it is possible to obtain a three-dimensional additive product with a net shape or near net shape.
  • Methods for determining whether there are defects in manufactured parts include, for example, non-destructive inspection methods such as internal defect detection using X-ray CT scanning and density measurement using Archimedes' method.
  • non-destructive inspection methods such as internal defect detection using X-ray CT scanning and density measurement using Archimedes' method.
  • the X-ray CT scanning method has a limited resolution for large parts.
  • the Archimedes method cannot detect individual defects and has low detection accuracy for a small number of defects.
  • Patent Document 2 discloses that the presence or absence of defects in an additive product is estimated using brightness data of light emitted from a molten pool formed when metal powder is melted.
  • Patent Document 1 WO2018/043349 WO2022/097651 publication
  • Patent Document 1 only determines whether fume or spatter has occurred by monitoring the external appearance. Furthermore, Patent Document 2 estimates defects in an additive product by using local signal abnormalities of the brightness average value and standard deviation for each layer of the additive product, and estimates the mechanical properties of the additive product, etc. No consideration had been given to how to estimate and evaluate this.
  • the present invention provides an additive product inspection method and an additive product manufacturing method that can estimate the mechanical properties of the additive product.
  • the method for inspecting an additive product of the present invention is a method for inspecting an additive product manufactured by melting and solidifying metal powder, and includes detecting light emitted from a molten pool formed when the metal powder is melted.
  • This is a method for inspecting an additive product, which is characterized by evaluating whether or not.
  • the variation range is a variation rate, and the variation rate is 18.0% or less.
  • the present invention includes a powder supply step of supplying metal powder, a modeling step of irradiating the metal powder with a heat source to melt and solidify the metal powder to shape an additive product, and forming the additive product when the metal powder is melted.
  • an evaluation step for estimating the mechanical properties of the additive product using the method and in the evaluation step, the evaluation data includes an average brightness value, a standard deviation of the average brightness value, and an inspection step comprising:
  • the evaluation data includes at least one of these moving average values, evaluates whether or not the evaluation data is within a predetermined variation range, and if it is within the variation range, continues the modeling process, and thereafter each process It is preferable to further include a selection step of repeating the steps and determining whether or not to continue the modeling process if it is outside the variation range.
  • the variation range is a variation rate, and the variation rate is 18.0% or less.
  • FIG. 1 is a schematic diagram illustrating a configuration of a powder bed fusion bonding (PBF) type additive manufacturing apparatus and an example of an additive manufacturing method.
  • FIG. 2 is a flowchart showing the flow of a method for manufacturing an additive product.
  • PPF powder bed fusion bonding
  • manufacturing of the additive product is started by melting and solidifying metal powder. Thereafter, a brightness data acquisition step (S101) of acquiring brightness data of light emitted from a molten pool formed when the metal powder is melted, and an evaluation data extraction step of extracting evaluation data from the brightness data. (S103), and an evaluation step (S105) of estimating the mechanical properties (hereinafter sometimes simply referred to as properties) of the additive product using the evaluation data.
  • S101 to S105 will be explained in detail below.
  • Brightness data acquisition step (S101) First, when a metal powder is irradiated with a heat source or the like to melt the metal powder and form a molten pool, brightness data of the light emitted from the molten pool (sometimes simply referred to as brightness data) is obtained.
  • the heat source can be a laser beam or the like.
  • the light used in this embodiment may be at least one of the following: reflected light when a laser beam is irradiated; light generated by a temperature rise in the molten pool or heat-affected zone; and plasma light generated when a metal vapor is irradiated with a laser beam and turned into plasma when melted. It is preferable to detect a luminance with high detection sensitivity. Specifically, it is preferable to detect light emitted from the molten pool and its vicinity, in other words, light with a wavelength of 600 nm or more and 1100 nm or less, and it is even more preferable to detect light with a wavelength of 800 nm or more and 1000 nm or less.
  • an sCMOS camera can be used as a method for acquiring (detecting) brightness data.
  • the number of pixels may be 50,000 or more, preferably 500,000 or more, and more preferably 4,000,000 or more.
  • the shooting speed may be about 1 frame per second, preferably 10 frames or more per second.
  • EOSTATE Exposure OT manufactured by EOS
  • the brightness acquired by the sCMOS camera (also referred to as OT brightness) may be the brightness in the near-infrared region during the modeling process.
  • the sCMOS camera may be provided with a bandpass filter that passes only frequencies in the near-infrared region.
  • EOSTATE Exposure OT photographs the area around the molten pool using an sCMOS camera installed obliquely above the modeling surface to obtain light brightness data.
  • the sCMOS camera is installed diagonally above the modeling surface, it can be converted into an observation image taken from above the modeling surface by correcting the shooting distance and shooting angle using software.
  • evaluation data extraction step (S103) Next, evaluation data is extracted from the luminance data acquired in the luminance data acquisition step (S101).
  • the evaluation data includes an average luminance value and a standard deviation of the average luminance value.
  • the average brightness value indicates the brightness unit in Gv, and the brightness is displayed in stages in blue for zero and red for the maximum value of 4.5 x 104 , and the brightness (color degree ) is the average value of the integrated values. That is, the average brightness value is the average value of the brightness values of each pixel of the brightness image (the average value of the brightnesses acquired in one pixel of the image). Further, the standard deviation of the brightness average value (sometimes referred to as the brightness standard deviation) indicates an evaluation of the variation in the brightness average value calculated for each layer. For example, when manufacturing an additive product using a powder bed fusion (PBF) method, the average brightness value of each layer may be obtained, and the standard deviation may be calculated from the average brightness value. Then, until the modeling process is completed, the average brightness value and the standard deviation of the average brightness value for each layer may be saved and recorded.
  • PPF powder bed fusion
  • the average brightness value of section B is higher than that of section A. If the average brightness value obtained when forming section A is Gv 0 and the average brightness value obtained when forming section B is Gv n , the difference between the average brightness values of section A and section B (Gv n -Gv 0 ) can be expressed as ⁇ Gv (unit: Gv). It can be said that ⁇ Gv indicates the fluctuation range (fluctuation width). In addition, when moving from section A to section B, the fluctuation range can be observed in a step-like manner, and this step difference can be said to be the fluctuation range, and the higher the step, the larger the fluctuation range.
  • the average brightness value of section A and section B used to calculate ⁇ Gv may be the difference between the average value of the brightness average values of the entire area A and the average value of the average brightness values of the entire area B, The difference between a part of the average brightness value of section A and a part of the average brightness value of section B may be used.
  • the upper limit of the fluctuation range can be, for example, 4170 Gv or less. This is because if it exceeds 4170 Gv, there is a possibility that the additive product will have reduced mechanical properties such as tensile strength and elongation. Preferably it is 3500 Gv or less, more preferably 3000 Gv or less, still more preferably 2500 Gv or less.
  • the variation range when using the standard deviation of the luminance average value will be explained.
  • the interval before the fluctuation is defined as interval A
  • the standard deviation of the luminance average value in interval A is Gv ⁇ 0
  • the interval after the fluctuation is defined as interval B.
  • the variation range is the difference (Gv ⁇ n - Gv ⁇ 0 ) between the standard deviation of the luminance average value of section A and section B as ⁇ Gv ⁇ (unit: Gv).
  • the transition from section A to section B is expressed in a step shape (step shape), and this step difference can also be said to be a fluctuation range.
  • the standard deviation of the luminance average values of section A and section B used for calculation is the standard deviation of the luminance average value of the entire section A and the luminance of the entire section B. It may be the difference between the standard deviations of the average values, or it may be the difference between the standard deviations of the average luminance values of part of section A and the standard deviations of the average luminance values of part of section B.
  • the variation range is preferably small, but the upper limit can be 1100 Gv or less. This is because if it exceeds 1100 Gv, there is a possibility that the additive product will have reduced mechanical properties such as tensile strength and elongation. Preferably it is 800 Gv or less, more preferably 500 Gv or less.
  • a moving average value (unit: Gv) calculated from the average brightness value or the standard deviation of the average brightness value can also be used.
  • a moving average value is an average value obtained for each certain interval in time-series data while shifting the interval. Evaluation using moving average values provides a smooth curve that represents long-term trends, making it easier to detect sudden changes.
  • it may be obtained by calculating a simple arithmetic mean of data.
  • the average brightness value or the standard deviation of the average brightness value can be calculated by adding up several pieces of data before and after the central data to be calculated.
  • the fluctuation range is small.
  • the upper limit can be 3800 Gv or less. This is because if it exceeds 3,800 Gv, the resulting additive product will have reduced mechanical properties, such as tensile strength and elongation. Preferably it is 3500 Gv or less, more preferably 3000 Gv or less, even more preferably 2000 Gv or less.
  • the upper limit is 970 Gv or less. This is because if it exceeds 970 Gv, it may result in an additive product with reduced mechanical properties, such as tensile strength and elongation.
  • it is 800 Gv or less, more preferably 600 Gv or less, even more preferably 500 Gv or less.
  • the standard deviation of the brightness average value, or their moving average value for example, a fluctuation rate (%) can also be used instead of the fluctuation range.
  • the fluctuation rate will be explained using FIG. 2.
  • the average brightness value Gv n when the average brightness value changes the average brightness value Gv 0 before the average brightness value changes to Gv n
  • the average brightness value Gv n minus Gv 0 the difference is ⁇ Gv
  • the fluctuation rate can be a value obtained by dividing ⁇ Gv by Gv 0 ( ⁇ Gv/Gv 0 ).
  • the variation rate is calculated by using luminance data such as the luminance average value acquired during the modeling process and using the amount of change in the luminance data observed during the modeling process as a slope.
  • luminance data such as the luminance average value acquired during the modeling process
  • the amount of change in the luminance data observed during the modeling process as a slope.
  • the fluctuation rate if there is a change in the average brightness value or the standard deviation of the average brightness value, for example, if there is a step-like change, the amount of change can be calculated as the slope, making evaluation easier. preferable.
  • the average brightness value changes temporarily and the rate of fluctuation becomes high, this may not affect the mechanical properties of the additive product depending on the subsequent change in the average brightness value. For example, if the average brightness value shows a peak top due to a sudden increase or decrease in value, the rate of fluctuation will become large due to a large change in the average brightness value, but the mechanical properties of the additive product may not be affected even if the average brightness value momentarily moves up and down. Therefore, additive manufacturing may continue even if a momentary peak top occurs in the average brightness value.
  • the fluctuation rate can be the value obtained by dividing ⁇ Gv ⁇ by Gv ⁇ 0 ( ⁇ Gv ⁇ /Gv ⁇ 0 ). It is preferable that the fluctuation rate is small, but the upper limit can be set to 18.0%. This is because if it exceeds 18.0%, the mechanical properties, such as tensile strength and elongation, of the additive product will be reduced. It is preferably 15.0% or less, more preferably 11.0% or less, and even more preferably 10.5% or less.
  • the fluctuation range and fluctuation rate may be set in advance.
  • a method for setting the variation range and variation rate in advance for example, the variation range and variation rate of brightness data acquired for an additive product (hereinafter referred to as a sample) produced in advance can be used as a threshold value. Specifically, if the evaluation result of the mechanical properties of the sample is good, the variation range or variation rate of the luminance data acquired when producing the sample can be used as the threshold value.
  • brightness data such as the average brightness value and the standard deviation of the average brightness value may change depending on the shape of the additive product, the modeling conditions (output, scanning speed, scanning pitch (scanning interval), layer thickness), etc. Therefore, it is sufficient to create an additive product with the same shape and under the same modeling conditions, obtain brightness data for the additive product or sample, and make appropriate changes based on this data.
  • the alloy powder that can be used in this embodiment is not particularly limited, but includes, for example, Ni-based alloy, Fe-based alloy, Co-based alloy, Ti-based alloy, Al-based alloy, W-based alloy, Mo-based alloy, and WC alloy.
  • a multi-component alloy (high entropy alloy) or the like can be used.
  • the alloy powder of this embodiment can be manufactured using, for example, a gas atomization method, a water atomization method, a jet atomization method, etc., but it is preferable to manufacture the alloy powder by a gas atomization method that facilitates obtaining spherical powder. .
  • the size (particle size) of the alloy powder is preferably such that the average particle size (D50) is 5 to 200 ⁇ m, and 10 to The thickness is more preferably 100 ⁇ m, and even more preferably 20 to 80 ⁇ m.
  • One embodiment of the method for manufacturing an additive product includes a powder supply step of supplying metal powder, a modeling step of irradiating the metal powder with a heat source to melt and solidify the metal powder to shape an additive product, and a step of supplying the metal powder.
  • a modeling process comprising: a brightness data acquisition step of acquiring brightness data of light emitted from a molten pool formed when the powder is melted; and an evaluation data extraction step of extracting evaluation data from the brightness data.
  • the evaluation data includes a brightness average value, It includes at least one of the standard deviation of the average luminance value and their moving average value, evaluates whether the evaluation data is within a variation range, and if it is within the variation range, continues the modeling process. , one of the characteristics is that each of the above steps is repeated thereafter. Each step will be explained in detail below using FIGS. 7 and 8.
  • a powder bed fusion bonding (PBF) method can be used for the additive manufacturing method of this embodiment.
  • the PBF method is an additive manufacturing method in which a powder bed is prepared by spreading metal powder, and only the part to be shaped is melted, solidified, or sintered by irradiation with a laser beam or electron beam that provides thermal energy.
  • SLM method selective laser melting
  • SLS method selective laser sintering
  • additive manufacturing can usually be performed in an inert atmosphere such as nitrogen.
  • the powder bed fusion bonding method can also use an electron beam as a heat source, and is called selective electron beam melting (SEBM method) or electron beam melting (EBM method). .
  • SEBM method selective electron beam melting
  • EBM method electron beam melting
  • a method using an electron beam as a heat source allows additive manufacturing under high vacuum.
  • Conditions for shaping (manufacturing) the additive product include, for example, layer thickness: 10 to 300 ⁇ m, laser output: 50 to 1000 W, scan speed: 100 to 5000 mm/s, scan interval: 0.05 to 0.5 mm.
  • the conditions may be selected as appropriate.
  • the thickness is preferably 0.05 to 0.12 mm.
  • FIG. 7 is a diagram showing an outline of an additive manufacturing apparatus 100 using a powder bed fusion bonding method as an example.
  • the additive manufacturing apparatus 100 includes a stage 102, a base plate 103, a powder supply container 104 for supplying metal powder 105 to the base plate 103, and a recoater 160 for forming a powder bed 107 on the base plate 103. It has an unmelted powder recovery container 111 for recovering metal powder, a laser oscillator 108, and a galvanometer mirror 110, metal powder 105 is supplied onto a base plate 103, and a powder bed 107 of a constant thickness is formed by a recoater 160. be done.
  • this device includes an sCMOS camera 113 that detects light emitted from a molten pool formed when the metal powder 105 is melted, and a device that converts the light detected by the sCMOS camera into brightness data and obtains the brightness data.
  • this is provided in a form that is shared with the evaluation data extraction device 114 that extracts evaluation data.
  • the stage 102 is lowered by a further thickness (for example, about 10 to 100 ⁇ m) of the additive product 101 to be additively manufactured.
  • metal (raw material) powder 105 is supplied from the powder supply container 104 to the base plate 103 on the upper surface of the stage 102, and the metal powder 105 is flattened by the recoater 160 to form a powder bed 107 (powder layer).
  • the additive product 101 to be manufactured is shaped into a desired shape based on shape information, for example, 2D slice data converted from 3D-CAD data.
  • shape information for example, 2D slice data converted from 3D-CAD data.
  • a heat source emitted from a laser oscillator 108 for example, a laser beam 109 emitted from the laser oscillator 108 through a galvanometer mirror 110, is irradiated onto the metal powder 105 on the powder bed 107 spread on the base plate 103. A small molten pool is formed.
  • the metal powder 105 is melted and solidified to form a 2D slice-shaped solidified layer 112. Note that the unmelted metal powder 105 may be collected in the unmelted powder collection container 111 and reused.
  • evaluation data extraction step: S207 From the luminance data acquired by the luminance data acquisition device and the evaluation data extraction device 114, at least one of the evaluation data, that is, the luminance average value, the standard deviation of the luminance average value, and their moving average value is extracted (output )do.
  • the evaluation data extraction step (S103) in the additive product inspection method of the present embodiment described above can be applied.
  • evaluation step: S209 the characteristics of the additive product are estimated and evaluated using at least one of the extracted average brightness value, standard deviation of the average brightness value, and moving average value thereof. Note that the evaluation step (S105) in the method for inspecting an additive product according to the present embodiment described above can be applied. If the result is satisfactory, each step (S201 to S207) is repeated until an additive product of the desired shape is obtained. Furthermore, if it can be determined that the properties of the additional product up to the nth solidified layer are good, each step (S201 to S207) may be continued.
  • the brightness average value, the standard deviation of the brightness average value, and their moving average value acquired in the brightness data acquisition step (S207) is within the above-mentioned fluctuation range. However, if it is within the variation range, it can be estimated that the mechanical properties of the additive product are good.
  • each step (S201 to S207) may be continued. Furthermore, the printing process is temporarily interrupted, the printing conditions and slice data are corrected, and from the n+1 layer, the printing process is restarted by reflecting the changed printing conditions and corrected slice data. , each step (S201 to S207) may be repeated to produce an additive product. Further, in each of the above steps, the fluctuation rate can be used as a comparison target instead of the fluctuation range.
  • selection step: S210 In addition, if there is a possibility that the abnormality level is outside the variation range and cannot be resolved by performing subsequent processing or heat treatment, or by correcting the modeling conditions or slice data, perform each of the above steps (S201 to S207).
  • a selection step S210 may be further provided as a step for determining whether to continue. In the selection step S210, it is determined whether or not to stop the modeling process when an abnormality is determined from the evaluation step.
  • the stage 102 When one layer of lamination (modeling) is completed, the stage 102 is lowered and new metal powder 105 is supplied onto the solidified layer 112 to form a new powder bed 107. This newly formed powder bed 107 is irradiated with a laser beam 109 to melt and solidify it, thereby forming a new solidified layer.
  • the desired additive product 101 can be manufactured by repeating the powder supply step (S201) and the modeling step (S203) and stacking the solidified layers 112.
  • the powder supply step (S201), the modeling step (S203), the brightness data acquisition step (S205), the evaluation data extraction step (S207), and the evaluation step (S209) are repeated to create the final additive product.
  • the inspection process may be performed after obtaining the information.
  • the characteristics of the additive product can be estimated (inspected) from the obtained luminance data even while the additive product is being shaped. ), that is, it is possible to manufacture additive products while estimating their properties in-process (in real time).
  • the additive product 101 is laminated on the base plate 103 and manufactured as one piece, so it is covered with the unmelted metal powder 105, so when it is taken out, the metal powder 105 and the additive product 101 are separated. After cooling, the unmelted metal powder 105 may be collected, and the additive product 101 and the base plate 103 may be taken out from the powder additive manufacturing apparatus 100. Thereafter, an additive product can be obtained by separating (cutting, etc.) the additive product 101 from the base plate 103.
  • the variation range in advance.
  • the brightness data obtained when an additive product with good characteristics was additively manufactured is obtained in advance, and from that brightness data, the brightness average value, the standard deviation of the brightness average value, and at least the moving average value of the brightness average value, Extract any one of the brightness average value, the standard deviation of the brightness average value, the difference between the brightness average values before and after the moving average value fluctuated greatly, the difference between the standard deviation of the brightness average value, and their moving average value. At least one of these can be used as a threshold value.
  • the average brightness value and the standard deviation of the average brightness value vary depending on the shape and modeling conditions of the additive product (laser output, scanning speed, scanning pitch (scanning interval), thickness, etc.), so the average brightness value set in advance
  • the range and the standard deviation range of the brightness average value may be changed as appropriate depending on the desired additive product.
  • the characteristics of the additive product can be estimated in-process, and the evaluation results can be newly updated.
  • Additive products can be used for manufacturing by applying additive manufacturing conditions. Since the characteristics of additive products can be estimated in-process, it is particularly effective in that it is possible to detect defective products early and take prompt action to prevent the recurrence of defects.
  • the additive manufacturing conditions can be applied in real time to modify the properties of the additive product during manufacturing, it can be expected to have the effect of suppressing the defect rate of the additive product. Further, for example, it is possible to simplify the inspection process in the post-process, thereby reducing manufacturing costs.
  • prismatic additive products F1 to F8 were produced in accordance with the order of the flowchart shown in FIG.
  • the brightness data acquisition (measurement) conditions were an sCMOS camera with a pixel count of 4 million pixels, a shooting speed of 10 frames per second (shooting speed: 100 msec, shooting frequency: 10 Hz), and the light to be detected was an alloy
  • the radiation was emitted from a molten pool formed by melting powder, and the detection wavelength band was 900 ⁇ 12.5 nm.
  • a Ni-Cr-Mo alloy having the alloy composition (unit: mass %) shown in Table 1 was used as the metal powder serving as the raw material.
  • This metal powder was prepared by preparing the raw materials of Ni, Cr, Mo, and Ta to have the alloy composition shown in Table 1, and granulating the powder by vacuum gas atomization. Thereafter, the granulated powder was sieved to have a particle size of 10 ⁇ m to 53 ⁇ m and an average particle size (d50) of about 35 ⁇ m.
  • Additive products F1 and F2 of 10 mm x 10 mm x height 40 mm were produced according to the flow shown in FIG. 8 .
  • the additive manufacturing conditions were a lamination (single layer) thickness of 0.06 mm, a laser output of 300 W, a laser scanning speed of 1200 mm/sec, and a scanning pitch of 0.09 mm.
  • Additive products F3 and F4 of 10 mm x 10 mm x 40 mm height (prism shape) were produced according to the flow of Fig. 8.
  • the additive manufacturing conditions were a layer (single layer) thickness of 0.08 mm, a laser output of 350 W, a laser scanning speed of 1150 mm/sec, and a scanning pitch of 0.09 mm.
  • Addition products F5 and F6 of 10 mm x 10 mm x height 40 mm were produced according to the flow shown in FIG. 8 .
  • the modeling conditions during additive manufacturing were the same as those for additive products F1 and F2.
  • Additive products F7 and F8 of 10 mm x 10 mm x height 40 mm (prismatic shape) were produced according to the flow shown in FIG. 8 .
  • the modeling conditions during additive manufacturing were the same as those for additive products F3 and F4.
  • Table 2 shows, for additive products F1 to F8, the average brightness value (hereinafter referred to as average brightness value (i)) from 22 to 24 mm and the average brightness value (hereinafter referred to as average brightness value (ii)) from 26 to 28 mm. )), the luminance average value difference (luminance average value (ii) - luminance average value (i), ⁇ Gv), and fluctuation rate (luminance average value difference/luminance average value (i)) are shown.
  • the luminance average value difference will be referred to as the variation range of the luminance average value.
  • Table 3 shows the standard deviation of the average brightness value from stacking heights of 22 to 24 mm (hereinafter referred to as the standard deviation (i) of the average brightness value) for the additive products F1 to F8, and the standard deviation of the average brightness value from 26 to 28 mm.
  • deviation hereinafter referred to as standard deviation of average brightness value (ii)
  • difference in standard deviation of average brightness value standard deviation of average brightness value (ii) - standard deviation of average brightness value (i), ⁇ Gv ⁇ )
  • fluctuation rate Difference in standard deviation of average brightness value/standard deviation of average brightness value (i)
  • the difference in the standard deviation of the brightness average value will be referred to as the variation range of the standard deviation of the brightness average value.
  • FIGS. 3 to 6 show changes in the average brightness values and the standard deviations of the average brightness values obtained when additively manufacturing the additive products F1 to F8.
  • the fluctuation range of the average brightness value was a maximum of 1927 Gv, which was less than 4100 Gv, and the fluctuation rate was a maximum of 0.2%, which was less than 18%.
  • the fluctuation range using the average brightness value exceeded 4000 Gv, and the fluctuation range of the standard deviation of the average brightness value also exceeded 18%.
  • the additive products F1 to F8 were evaluated for tensile strength, yield strength, and elongation at break.
  • each of the additive products F1 to F8 was cut into tensile test pieces (parallel part diameter: 3 mm, length between gauges: 7 mm) in accordance with the standard test (ASTM E8). were used as test pieces FT1 to FT8.
  • a tensile test (INSTRON 5982, Instron Corporation) was conducted on test pieces FT1 to FT8 at room temperature (22° C.) to determine the average value of tensile strength and 0.2% proof stress. Further, the elongation was determined as a percentage by comparing the test pieces after the test, measuring the gauge length, and dividing by the original gauge length. The results are shown in Table 4.
  • the break position A refers to the case where the break position is within 1/4 of the gauge distance from the center between the gauge marks
  • the break position C refers to the case where the break position is outside the gauge mark.
  • test pieces FT1, FT2, FT5 and FT6 which were made using additive products F1, F2, F5 and F6 under the same additive manufacturing conditions, it was confirmed that FT5 and FT6 had lower 0.2% yield strength, tensile strength and elongation than FT1 and FT2. In particular, elongation was significantly lower.
  • test pieces FT3, FT4, FT7 and FT8, which were made using additive products F3, F4, F7 and F8 under the same additive manufacturing conditions, it was confirmed that FT7 and FT8 had lower 0.2% yield strength, tensile strength and elongation than FT3 and FT4. In particular, elongation was significantly lower.
  • FT1 to FT6 were 900 MPa or more, and especially FT1 to FT4 were 930 MPa or more. Furthermore, it was confirmed that FT1 to FT6 had an elongation of 40% or more, and in particular, FT1 to FT4 had an elongation of 59% or more. These mechanical property values can be said to be excellent values.
  • F7 and F8 as shown in Figure 6, the transition of the luminance average value in the section where the fluctuation range of the luminance average value fluctuated by 4000 Gv or more is 200, and the fluctuation range of the standard deviation of the luminance average value exceeds 1100 Gv.
  • the transition of the standard deviation of the luminance average value in the fluctuated section is illustrated as 210.
  • F7 and F8 include sections in which the variation range of the average luminance value obtained in the modeling process fluctuated by 4170 Gv or more, and the variation range of the standard deviation of the luminance average value exceeds 1107 Gv.
  • the fluctuation rate using the average brightness value is 18.0% at F7 and 21.7% at F8, and the fluctuation rate using the standard deviation of the average brightness value is also 18.0% at F7. .2%, and 20.4% at F8. Therefore, it can be inferred that the mechanical properties of F7 and F8 deteriorate when the modeling process and inspection process are repeated based on the variation range and variation rate.
  • moving average values and moving average value differences were also calculated using the luminance average values obtained when F6 and F7 were additively manufactured.
  • Moving average value from stacking height 22 to 24 mm hereinafter referred to as moving average value (i)
  • moving average value from 26 to 28 mm hereinafter referred to as moving average value (ii)
  • moving average value from moving average value (ii) When the moving average value difference (i) is the value obtained by subtracting the value (i), the moving average value (i) in the case of F6 is 18347Gv, the moving average value (ii) is 20262Gv, and the moving average value difference (i) is It was 1915Gv.
  • the moving average value (i) was 23178 Gv
  • the moving average value (ii) was 26984 Gv
  • the moving average value difference (i), that is, the fluctuation range using the moving average value was 3806 Gv. Therefore, it was confirmed that the mechanical properties of additive products can be estimated from the variation range of the moving average value using the brightness average value, as well as when using the brightness average value or the standard deviation of the brightness average value.
  • the moving average value and the moving average value difference were calculated using the standard deviation of the average brightness value obtained when additively manufacturing F6 and F7.
  • the moving average value from 22 to 24 mm in the stacking height was the moving average value (iii)
  • the moving average value from 26 to 28 mm was the moving average value (iv)
  • the value obtained by subtracting the moving average value (iii) from the moving average value (iv) was the moving average value difference (ii).
  • the moving average value (iii) was 4432 Gv
  • the moving average value (iv) was 4864 Gv
  • the moving average value difference (ii) was 432 Gv.
  • the moving average value (iii) was 6109 Gv
  • the moving average value (iv) was 7088 Gv
  • the moving average value difference (ii) that is, the fluctuation range of the moving average value using the standard deviation of the average brightness value, was 979 Gv. Therefore, it was confirmed that the mechanical properties of the additively manufactured product can be estimated from the fluctuation range of the moving average value using the standard deviation of the average brightness value, just like the fluctuation range using the standard deviation of the average brightness value.
  • Additive manufacturing device 101 Additive product 102: Stage 103: Base plate 104: Powder supply container 105: Metal powder 107: Powder bed (powder layer) 108: Laser oscillator 109: Laser beam 110: Galvanometer mirror 111: Unmelted powder recovery container 112: 2D slice-shaped solidified layer 113: sCMOS camera 114: Luminance data acquisition device and evaluation data extraction device 160: Recoater 200: Change in brightness average value 210: Change in standard deviation of brightness average value

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Abstract

La présente invention concerne un procédé d'inspection d'un produit fabriqué de manière additive et un procédé de fabrication d'un produit fabriqué de manière additive qui sont en mesure d'estimer des propriétés mécaniques d'un produit fabriqué de manière additive.　L'invention concerne un procédé d'inspection d'un produit fabriqué de manière additive qui est fabriqué par fusion et solidification de poudre métallique, le procédé étant caractérisé en ce qu'il comprend : une étape d'acquisition de données de luminance pour acquérir des données de luminance concernant la lumière émise à partir d'un bain fondu formé lorsque la poudre métallique a été fondue ; une étape d'extraction de données d'évaluation pour extraire des données d'évaluation à partir des données de luminance ; et une étape d'évaluation pour utiliser les données d'évaluation pour estimer des propriétés mécaniques du produit fabriqué de manière additive, dans l'étape d'évaluation, les données d'évaluation comprenant au moins l'une parmi la valeur moyenne de luminance, l'écart-type de la valeur moyenne de luminance et les valeurs moyennes mobiles de ces valeurs, et une évaluation est réalisée pour établir si les données d'évaluation se trouvent ou non dans une plage de variation.
PCT/JP2023/034367 2022-09-22 2023-09-21 Procédé d'inspection de produit fabriqué de manière additive et procédé de fabrication de produit fabriqué de manière additive WO2024063150A1 (fr)

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2018536092A (ja) * 2015-11-16 2018-12-06 レニショウ パブリック リミテッド カンパニーＲｅｎｉｓｈａｗ Ｐｕｂｌｉｃ Ｌｉｍｉｔｅｄ Ｃｏｍｐａｎｙ 付加製造方法および装置
WO2020026306A1 (fr) * 2018-07-30 2020-02-06 三菱電機株式会社 Dispositif de commande de condition de stratification
JP2021009126A (ja) * 2019-07-03 2021-01-28 株式会社ジェイテクト 付加製造物の品質推定装置
WO2022097651A1 (fr) * 2020-11-04 2022-05-12 日立金属株式会社 Procédé pour la prévision de défaut de produit fabriqué de manière additive et procédé pour la fabrication de produit fabriqué de manière additive

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2018536092A (ja) * 2015-11-16 2018-12-06 レニショウ パブリック リミテッド カンパニーＲｅｎｉｓｈａｗ Ｐｕｂｌｉｃ Ｌｉｍｉｔｅｄ Ｃｏｍｐａｎｙ 付加製造方法および装置
WO2020026306A1 (fr) * 2018-07-30 2020-02-06 三菱電機株式会社 Dispositif de commande de condition de stratification
JP2021009126A (ja) * 2019-07-03 2021-01-28 株式会社ジェイテクト 付加製造物の品質推定装置
WO2022097651A1 (fr) * 2020-11-04 2022-05-12 日立金属株式会社 Procédé pour la prévision de défaut de produit fabriqué de manière additive et procédé pour la fabrication de produit fabriqué de manière additive

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