Monitoring Systems and Additive Manufacturing Systems

Abstract

To provide a monitoring system and an additive manufacturing system by which it is easier to recognize quality of an additively manufactured article.SOLUTION: A monitoring system in an embodiment includes a collection device and a processing device. The collection device collects information about a coagulated part coagulated during an additive manufacturing for forming a plurality of layers by repeating melting and coagulation of metal powder. The processing device determines the present or absence of a fracture in the coagulated part by using the information, and generates quality data indicating the presence or absence of the fracture.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] Embodiments of the present invention relate to a monitoring system and an additive manufacturing system. [Background technology]

[0002] There are additive manufacturing devices that manufacture objects using additive manufacturing, in which metal powder is melted and solidified repeatedly to add layers at a time. There is a demand for technology that makes it easier to grasp the quality of additively manufactured objects. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2020-15944 A Summary of the Invention [Problem to be solved by the invention]

[0004] The problem that the present invention aims to solve is to provide a monitoring system and an additive manufacturing system that can more easily grasp the quality of additively manufactured articles. [Means for solving the problem]

[0005] According to an embodiment, the monitoring system includes a collection device and a processing device, the collection device collects information of a solidified portion during additive manufacturing in which a metal powder is repeatedly melted and solidified to form multiple layers, and the processing device uses the information to determine the presence or absence of defects in the solidified portion and generates quality data indicative of the presence or absence of the defects. [Brief description of the drawings]

[0006] [Figure 1] FIG. 1 is a schematic diagram illustrating an additive manufacturing system according to an embodiment. [Diagram 2] FIG. 1 is a block diagram illustrating a configuration of a monitoring system according to an embodiment. [Diagram 3] FIG. 2 is a block diagram showing a control system of an additive manufacturing device. [Figure 4] FIG. 1 is a schematic diagram showing additive manufacturing. [Diagram 5] FIG. 2 is a schematic diagram illustrating an image obtained by an imaging device. [Figure 6] FIG. 2 is a schematic diagram for explaining an imaging region. [Figure 7] 1 is a flowchart showing the operation of the monitoring system according to the embodiment. [Figure 8] FIG. 1 is a block diagram showing a configuration of an additive manufacturing system according to an embodiment. [Figure 9] 1 is a flowchart showing the operation of the monitoring system according to the embodiment. [Figure 10] 1 is a flowchart showing the operation of the monitoring system according to the embodiment. [Figure 11] FIG. 2 is a schematic diagram illustrating a hardware configuration. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] Hereinafter, embodiments of the present invention will be described with reference to the drawings. The drawings are schematic or conceptual, and the relationship between the thickness and width of each part, the size ratio between parts, etc. are not necessarily the same as those in reality. Even when the same part is shown, the dimensions and ratios of each part may be different depending on the drawing. In this specification and each drawing, elements similar to those already explained are given the same reference numerals and detailed explanations are omitted as appropriate.

[0008] FIG. 1 is a schematic diagram illustrating an additive manufacturing system according to an embodiment. FIG. 2 is a block diagram showing a configuration of a monitoring system according to an embodiment. FIG. 3 is a block diagram showing the control system of the additive manufacturing device. As shown in FIG. 1, the additive manufacturing system 2 includes a monitoring system 1 and an additive manufacturing apparatus 100.

[0009] As shown in FIG. 1, the additive manufacturing apparatus 100 includes a first container 110, a first stage 111, a second container 120, a second stage 121, a coater 130, an irradiation device 140, and an optical system 141.

[0010] Inside the first container 110, a powder bed 205 on which metal powder 201 is laid is provided. The additive manufacturing apparatus 100 partially melts the metal powder 201 provided on the upper surface of the powder bed 205. The molten metal powder 201 solidifies to form a solidified layer. Another solidified layer is repeatedly added on top of the solidified layer and joined together to form a solidified portion 210. Finally, an article made of the solidified portion 210 is manufactured.

[0011] The irradiation device 140 irradiates the metal powder 201 in the first container 110 with laser light 150. The irradiation device 140 may emit an electron beam. The laser light 150 is reflected by the optical system 141 and irradiated onto a part of the powder bed 205. By driving the optical system 141, the laser light 150 is irradiated onto an arbitrary position of the powder bed 205.

[0012] The second container 120 stores the metal powder 201 to be supplied to the first container 110. A first stage 111 is provided at the bottom of the first container 110. A second stage 121 is provided at the bottom of the second container 120. The first stage 111 and the second stage 121 are movable up and down. When the first stage 111 rises or falls, the height of the upper surface of the powder bed 205 and the height of the upper surface of the solidification portion 210 change. When the second stage 121 rises or falls, the height of the upper surface of the metal powder 201 stored in the second container 120 changes.

[0013] When the metal powder 201 is melted by the laser light 150 and a new solidified layer is added to the solidified portion 210, the first stage 111 descends. The upper surface of the powder bed 205 and the upper surface of the solidified portion 210 are located below the upper surface of the first container 110. After that, the second stage 121 ascends. The upper surface of the metal powder 201 stored in the second container 120 is located above the upper surface of the second container 120. The coater 130 moves from the second container 120 toward the first container 110. The coater 130 carries the metal powder 201 located above the upper surface of the second container 120 toward the first container 110. The coater 130 supplies a new layer of metal powder 201 on the powder bed 205 and the solidified portion 210.

[0014] The monitoring system 1 collects information during additive manufacturing by the additive manufacturing apparatus 100. The monitoring system 1 uses the information to determine the presence or absence of a defect in the solidified portion 210. Furthermore, the monitoring system 1 generates quality data indicating the presence or absence of a defect based on the determination result. As shown in FIG. 1, the monitoring system 1 includes an imaging device 21, a temperature sensor 22, and a lighting device 23.

[0015] The imaging device 21 is, for example, a camera, and captures an image of the state of the first container 110 during additive manufacturing. The imaging device 21 captures images of the powder bed 205, the solidified portion 210, the molten pool 220 generated by melting the metal powder 201, the laser light 150 hitting the surface of the powder bed 205, etc. In this way, images showing the state during additive manufacturing are collected as the information.

[0016] The temperature sensor 22 measures the temperature of the powder bed 205, the solidified portion 210, or the molten pool 220. In this way, the temperature of each portion during additive manufacturing, the overall temperature distribution, etc. are collected as the information. The temperature sensor 22 measures the temperature of the target based on, for example, infrared rays emitted from the target.

[0017] The illumination device 23 illuminates the powder bed 205 so that the imaging device 21 can obtain a clearer image. An optical system for adjusting the imaging position of the imaging device 21 and the illumination position of the illumination device 23 may be provided as appropriate.

[0018] FIG. 2 is a schematic diagram illustrating a configuration of a monitoring system according to an embodiment. As shown in FIG. 2, the monitoring system 1 according to the embodiment further includes a processing device 11, an input device 12, a display device 13, and a storage device .

[0019] The processing device 11 generates quality data based on information collected by the imaging device 21 and the temperature sensor 22. The input device 12 is used when a user inputs data to the processing device 11. The display device 13 displays data output from the processing device 11 to the user. The storage device 14 stores data. For example, the imaging device 21 and the temperature sensor 22 save the acquired information in the storage device 14. The processing device 11 accesses the storage device 14 and acquires the information.

[0020] The operations of the imaging device 21, the temperature sensor 22, and the lighting device 23 may be controlled by the processing device 11 or by a separate control device.

[0021] FIG. 3 is a schematic diagram showing the control system of an additive manufacturing device. 3, the additive manufacturing apparatus 100 further includes a control device 101. The operations of the first stage 111, the second stage 121, the coater 130, the irradiation device 140, and the optical system 141 are controlled by the control device 101. The control device 101 refers to preset additive manufacturing conditions and operates each component according to the conditions.

[0022] FIG. 4 is a schematic diagram showing additive manufacturing. In Fig. 4, a laser beam 150 as a heat source is irradiated onto a part of a powder bed 205, and the metal powder 201 is melted. The heat source may be an electron beam. The molten metal powder 201 forms a molten pool 220. The molten metal powder 201 solidifies to form a solidified portion 210.

[0023] The solidified portion 210 includes a plurality of beads 211. The beads 211 extend along a first direction D1 in which the laser light 150 is scanned. The plurality of beads 211 are aligned in a second direction D2 perpendicular to the first direction D1.

[0024] When one or more beads 211 are formed in a layer of metal powder 201 extending along the first direction D1 and the second direction D2, a new layer of metal powder 201 is provided in a third direction D3. The third direction D3 is perpendicular to the first direction D1 and the second direction D2. In the new layer of metal powder 201, another bead is formed.

[0025] The imaging device 21 images one or more beads 211 and the molten pool 220 during irradiation with the laser beam 150. The imaging device 21 may image the powder bed 205 before irradiation with the laser beam 150. The imaging device 21 may image the powder bed 205 and the solidified portion 210 after irradiation with the laser beam 150 and before new metal powder 201 is supplied.

[0026] FIG. 5 is a schematic diagram showing an image obtained by the imaging device. 5 (first image) shows the laser beam 150, the metal powder 201, the beads 211a to 211c, and the molten pool 220. The bead 211b (second bead) is formed before the bead 211a (first bead). The bead 211c is formed before the bead 211b. The bead 211b is located between the beads 211a and 211c and is adjacent to the beads 211a and 211c.

[0027] 5, the processing device 11 extracts data characteristic of additive manufacturing from the image. For example, the processing device 11 extracts first data including one or more data selected from the width W1 of the bead 211a immediately after solidification, the outline of the bead 211a, the surface shape of the bead 211a, the width W2 of the bead 211b, the outline of the bead 211b, the surface shape of the bead 211b, the width W3 of the bead 211c, the outline of the bead 211c, the surface shape of the bead 211c, the outline of the molten pool 220, and the size of the laser beam 150.

[0028] "Just after solidification" refers to the bead 211 on the line scanned by the laser beam 150. The bead 211 just after solidification is aligned with the molten pool 220 in the first direction D1. The width of the bead 211a, 211b, or 211c corresponds to the length of the bead 211a, 211b, or 211c in the second direction D2. As the surface shape, at least one selected from the size and position of a local depression (hole defect), surface roughness, and luster (brightness) is used. The size of the laser beam 150 is represented by the area of ​​a region surrounded by the outline of the laser beam 150.

[0029] The storage device 14 may store a first model for extracting first data from an image. The first model includes, for example, a neural network. The processing device 11 inputs an image to the first model and acquires first data output from the first model. For example, when the image shown in FIG. 5 is input, the first model outputs line segments Li1 to Li3. The line segment Li1 is the boundary between the bead 211a and the metal powder 201 and the boundary between the bead 211a and the bead 211b, and indicates the outline of the bead 211a. The line segment Li2 indicates the outline of the laser beam 150. The line segment Li3 indicates the outline of the molten pool 220.

[0030] When the processing device 11 acquires the first data, it refers to the database stored in the storage device 14. The database includes conditions for determining the presence or absence of a defect based on the first data.

[0031] As one example, in an area where a defect exists, the width of one of the beads 211 changes locally. When the width is less than a preset threshold, it is determined that the area has a defect. As another example, when the size of the laser light 150 is small, a sufficient amount of the metal powder 201 is not melted, and defects are likely to occur. When the size is less than a preset threshold, it is determined that the area has a defect.

[0032] For example, the processing device 11 extracts, as the first data, a plurality of data including the outline of the bead 211a, the outline of the molten pool 220, and the size of the laser beam 150. The database includes conditions for each of the outline of the bead 211a, the outline of the molten pool 220, and the size of the laser beam 150. The processing device 11 compares each of the plurality of data with a plurality of conditions to determine the presence or absence of a defect.

[0033] The database may include information regarding the type of defect. For example, the defect may be an undercut where the solidified portion 210 is locally thin, an overlap where the solidified portion 210 is locally thick, or a spatter formed by scattering of molten metal. For one data, a plurality of conditions corresponding to a plurality of types of defects are set. The processing device 11 determines the presence or absence of a defect and the type of the defect based on the plurality of conditions included in the database.

[0034] The presence of a defect may be expressed by a probability. For example, one or more conditions are set for each data. For each condition, a probability of the presence of a defect is set. When a condition is met, it is determined that a defect exists with the set probability. When multiple conditions are met, the probability of the presence of a defect increases.

[0035] 6(a) and 6(b) are schematic diagrams for explaining the imaging region. 6(a) shows an initial layer A1 of metal powder 201 provided in the first container 110. The layer A1 is divided into a plurality of regions B in a first direction D1 and a second direction D2. 11 ~B xy In the illustrated example, x number of regions B are arranged in the first direction D1, and y number of regions B are arranged in the second direction D2. The imaged range C is set to be larger than one region B. The image capturing device 21 captures the regions B 11 ~B xy When the laser beam 150 is irradiated onto each of the layers A1, images of the laser beam 150, the solidified portion 210, and the molten pool 220 are captured. In this way, x×y images of the layer A1 are acquired.

[0036] The imaging device 21 repeats the imaging for each layer in the same manner. For example, FIG. 6B shows the zth layer A of the first container 110. z The imaging device 21 represents layer A. z In the same manner as in layer A1, in region B 11 ~B xy When each of the points is irradiated with laser light 150, an image is taken.

[0037] A plurality of images are acquired at different imaging positions in the first direction D1, the second direction D2, or the third direction D3 by the imaging device 21. The processing device 11 determines the presence or absence of defects in each of the plurality of imaging regions based on the plurality of images.

[0038] The processing device 11 may determine the presence or absence of a defect based on the difference between multiple images. Typically, the number of areas determined to have a defect is smaller than the number of areas determined to have no defect. The difference between images of areas determined to have no defect is relatively small. The difference between an image of an area determined to have no defect and an image of an area determined to have a defect is relatively large.

[0039] For example, the processing device 11 inputs a new image and one or more past images into the first model, and obtains line segments Li1 to Li3 corresponding to the respective images. The processing device 11 calculates the difference in feature amount between the multiple images for the line segments Li1 to Li3. The processing device 11 compares the difference with a preset condition, and judges the presence or absence of a defect in the area captured in the new image.

[0040] Alternatively, a reference image when there is no defect may be stored in advance in the storage device 14. The processing device 11 calculates the difference between the new image and the reference image. Based on the difference, the processing device 11 determines whether or not there is a defect in the area captured in the new image.

[0041] The processing device 11 is a layer A1-A zFor example, the processing device 11 may calculate a difference between images of the region B that are located at the same position in the first direction D1 and the second direction D2. z Area B 11 Image of layers A1-A z-1 Area B 11 The difference between the image of and is calculated.

[0042] For example, the processing device 11 calculates one or both of the difference in brightness and the difference in contrast value as the difference. In calculating the difference, the processing device 11 may perform a calculation such as differentiating adjacent pixel regions to calculate the contrast gradient, quantitatively calculating periodicity by Fourier transform, or simply calculating the difference in shading. A pixel region is a region consisting of one or more pixels. A threshold is set in advance as a condition for the difference. When the difference is larger than the threshold, the processing device 11 determines that the region captured in the new image has a defect.

[0043] The imaging device 21 may capture an image (second image) of the powder bed 205 after a new layer of metal powder 201 is supplied and before the laser light 150 is irradiated. For example, the processing device 11 calculates the position of each point of the powder bed 205 in the third direction D3 and their average position from the obtained image. A "point" is a part of an "area". The processing device 11 calculates the distance (difference) between the position of each point and the average position. A condition (threshold) for the distance is set in advance. If the distance exceeds the threshold, it indicates that the surface of the solidified portion 210 formed at that point is locally depressed or raised. The processing device 11 determines that there is a defect in the solidified portion 210 immediately below the point where the distance exceeds the threshold. In addition, when the metal powder 201 at the point where the distance exceeds the threshold solidifies, there is a high possibility that a defect will occur. For this reason, it may be considered that there is (will occur) a defect at the point where the distance exceeds the threshold. The imaging device 21 may include a depth sensor so that the position in the third direction D3 can be acquired with higher accuracy.

[0044] For example, the imaging device 21 images the powder bed 205 at multiple positions in the first direction D1 and the second direction D2. The processing device 11 aligns and stitches the images in the first direction D1 and the second direction D2 to obtain a single overall image. The processing device 11 calculates the distance between the position of each point and the average position in the single overall image.

[0045] The imaging device 21 may capture an image (third image) of the solidified portion 210 after irradiation with the laser light 150 and before a new layer of metal powder 201 is supplied. For example, the processing device 11 joins together images of each region of the solidified portion 210 to obtain one overall image. From the obtained images, the processing device 11 calculates the position of each point of the solidified portion 210 in the third direction D3 and their average position. The processing device 11 calculates the distance (difference) between the position of each point and the average position. A condition (threshold) for the distance is set in advance. The processing device 11 determines that there is a defect at a point where the distance exceeds the threshold.

[0046] The processing device 11 may detect spatters present on the solidified portion 210 from the entire image. For example, a region whose position in the third direction D3 is higher than the average position by a predetermined threshold value is counted as a spatter. The processing device 11 determines the region in which the spatters are detected as a defective region. The processing device 11 may determine the region in which more than a specified number of spatters are present within a preset area as a defective region. Furthermore, if the metal powder 201 solidifies on the region in which the spatters are present, there is a high possibility that a defect will occur. For this reason, the region located above the region in which the spatters are present may be considered to have (will occur) a defect.

[0047] A plurality of imaging devices 21 may be provided. For example, an imaging device 21 that images each region during irradiation with the laser light 150 and another imaging device 21 that images the powder bed 205 or the solidified portion 210 before or after irradiation with the laser light 150 may be provided.

[0048] The temperature sensor 22 measures the temperature of each part during additive manufacturing. For example, the temperature sensor 22 measures the temperature of the bead 211a, the bead 211b, the bead 211c, or the molten pool 220 immediately after solidification, as shown in FIG. 5, and generates second data indicating the temperature.

[0049] When the processing device 11 acquires the second data, it refers to a database stored in the storage device 14. The database includes conditions for determining the presence or absence of a defect based on the second data. For example, the database includes conditions (thresholds) for each of the temperature of the bead 211a, the temperature of the bead 211b, the temperature of the bead 211c, and the temperature of the molten pool 220. The processing device 11 compares each of the multiple temperatures included in the second data with the multiple conditions to determine the presence or absence of a defect. As an example, if the temperature of the bead 211a or the temperature of the molten pool 220 immediately after solidification is lower than the threshold, it is determined that there is a defect.

[0050] For example, if the temperature of any of the beads 211a, 211b, and 211c is lower than a threshold value, the temperature difference between the beads 211a, 211b, and 211c may cause cracks or thermal distortion in the solidified portion 210. Furthermore, if the width of any of the beads changes, the molding density changes. If the change in molding density is large, poor welding or voids leading to poor welding occur, causing defects.

[0051] The database may include information regarding the type of defect. For example, a plurality of conditions corresponding to a plurality of types of defects are set for the temperature of the bead 211a, the bead 211b, or the molten pool 220, respectively. The processing device 11 determines the presence or absence of a defect and the type of the defect based on the plurality of conditions included in the database. The presence of a defect may be indicated by a probability. For example, a plurality of conditions are set for a plurality of data, respectively. For each condition, a probability of the presence of a defect is set in advance. When the condition is satisfied, it is determined that a defect exists with the set probability. When a plurality of conditions are satisfied, the probability of the presence of a defect increases.

[0052] The temperature sensor 22, like the imaging device 21, measures the temperature in each region of each layer by following the irradiation of the laser light 150. For example, in the region B shown in FIG. 11 ~B xy When the laser beam 150 is irradiated onto each of the beads 211a, 211b, and the molten pool 220, the temperature sensor 22 measures the temperatures of the beads 211a, 211b, and the molten pool 220.

[0053] The temperature sensor 22 may measure the temperature of each area of ​​the powder bed 205 after a new layer of metal powder 201 is supplied and before the laser light 150 is irradiated. For example, the processing device 11 generates a temperature distribution in the powder bed 205 from a plurality of measurement results. The processing device 11 calculates the average temperature, temperature variation, and the like from the temperature distribution. The processing device 11 compares the calculated value with a preset condition (threshold value) to determine the presence or absence of a defect.

[0054] The temperature sensor 22 may measure the temperature of each region after irradiation with the laser light 150 and before a new layer of metal powder 201 is supplied. The processing device 11 generates a temperature distribution in the powder bed 205 and the solidification portion 210 from multiple measurement results.

[0055] For example, if the temperature distribution is large, it may cause a bias in residual stress and uneven shape in the layer. If the temperature distribution is equal to or greater than a preset threshold, there is a high possibility that molding defects will occur in the layer and adjacent layers above and below. The processing device 11 determines that the layer and the adjacent layers have defects.

[0056] The processing device 11 stores the determination result in the storage device 14. If it is determined that there is a defect, the processing device 11 stores the position of the defect in the storage device 14. If it is determined that there is a defect, the processing device 11 may link the image used for the determination to the determination result and the position of the defect. For example, the quality data includes, for a manufactured article, the result of the determination of the presence or absence of a defect, the position of the defect, and the image used to determine the presence of the defect.

[0057] FIG. 7 is a flowchart showing the operation of the monitoring system according to the embodiment. A collection device collects information during additive manufacturing (step S1). A processing device 11 acquires the collected information (step S2). The processing device 11 uses the information to determine the presence or absence of a defect at the location where the information was collected (step S3). In the determination, each data included in the collected information is compared with a preset condition. The processing device 11 generates quality data indicating the presence or absence of a defect (step S4).

[0058] Advantages of the embodiment will be described. An article manufactured by additive manufacturing may have defects. An example of an article defect is a void. The presence or absence of defects and the number of defects relate to the quality of the article. If there are defects or a large number of defects, the quality is deemed poor. The quality affects, for example, the price of the article, the target of application of the article, etc. Or, an article with poor quality is excluded from trading. In other words, it is preferable to be able to grasp the quality of a manufactured article in order to determine the price, target of application, whether or not the article can be traded, etc.

[0059] There is also a method of non-destructively testing manufactured products to check for defects and the number of defects. However, this method requires time and money for the inspection. For this reason, there is a demand for a technology that can grasp the quality of products more easily.

[0060] According to the monitoring system 1 of the embodiment, the collection device collects information during additive manufacturing. The collection device is an imaging device 21 or a temperature sensor 22. Using the collected information, the processing device 11 determines whether or not there is a defect. The processing device 11 also generates quality data including the determination result.

[0061] By collecting information during additive manufacturing, there is no need to provide a separate inspection step after the article is manufactured. Also, by reviewing the quality data, a user can determine the possibility of defects in the manufactured article. For example, a user can determine the possibility of the presence of defects, the number of defects that may exist, etc. According to the embodiment, the quality of an additively manufactured article can be more easily determined.

[0062] Moreover, the monitoring system 1 according to the embodiment can be added later to an already existing additive manufacturing apparatus 100. By adding the monitoring system 1 to an already existing additive manufacturing apparatus 100, the required cost can be reduced compared to the case of purchasing a new additive manufacturing apparatus with a built-in defect determination function.

[0063] The quality data preferably includes the location of defects in the manufactured article, allowing a user to easily grasp where in the article a defect may exist. The quality data also preferably includes an image used to determine the defect, allowing a user to easily confirm the accuracy of the determination result by the processing device 11. The location of the defect may be marked in the image, allowing a user to easily grasp the location of the defect in the image.

[0064] The processing device 11 may use a second model for determining the presence or absence of a defect, instead of a determination based on a preset condition. The second model includes, for example, a neural network. When the processing device 11 acquires the first data or the second data, the processing device 11 inputs the first data or the second data to the second model. The second model outputs data indicating the presence or absence of a defect. The processing device 11 acquires the output of the second model as a determination result. The second model is trained using a plurality of training data. The training data includes the first data, the second data, and labels for those data. The labels indicate the presence or absence of a defect and the type of defect.

[0065] The processing device 11 may obtain a final judgment result by combining the judgment based on the preset conditions and the judgment based on the second model. For example, when it is judged that there is a defect based on the preset conditions, the processing device 11 judges that there is a defect in that area. Even when it is judged that there is no defect based on the preset conditions, the processing device 11 inputs the first data or the second data to the second model. When the second model indicates the presence of a defect, the processing device 11 judges that there is a defect in that area. By combining the second model, it becomes possible to more accurately judge the presence of a defect that is difficult to judge based on the conditions alone.

[0066] FIG. 8 is a block diagram showing the configuration of an additive manufacturing system according to an embodiment. In the additive manufacturing system 2, the processing conditions of the additive manufacturing apparatus 100 may be changed according to the determination result by the monitoring system 1. Specifically, when it is determined that there is a defect, the processing device 11 changes the processing conditions of additive manufacturing. The processing device 11 stores the changed processing conditions in the storage device 14. The control device 101 controls each component of the additive manufacturing apparatus 100 according to the changed processing conditions.

[0067] For example, it is determined that a defect exists in a part of the region of the bead 211. When the laser beam 150 is irradiated to another region adjacent to the defect, the processing conditions are changed. This may correct the defect. As an example, when it is determined that an undercut exists based on the first data, the irradiation time is extended or the irradiation energy is increased when the laser beam 150 is irradiated to the adjacent region. This may cause a part of the metal powder 201 melted in another region to flow into the region with the undercut, correcting the undercut.

[0068] The database includes information regarding processing conditions in additive manufacturing. The database includes correspondence between values ​​of the first data and processing conditions. When it is determined that there is a defect, the processing device 11 accesses the database. The processing device 11 acquires processing conditions corresponding to the first data used in the determination. The processing device 11 stores the acquired processing conditions in the storage device 14. As a result, the preset processing conditions are changed to processing conditions for correcting the defect. The control device 101 controls the additive manufacturing device 100 according to the changed processing conditions.

[0069] The processing conditions may be changed depending on the type and severity of the defect. For example, if the undercut depression is large, the irradiation time is extended or the irradiation energy is increased when irradiating another area with the laser light 150. This increases the amount of melted metal powder 201, making it easier for the molten metal to flow to the undercut. This increases the possibility of the defect being repaired.

[0070] The possibility of correction may be set for each type of first data. When the processing device 11 determines that there is a defect, it accesses the database and refers to the possibility of correction for the first data on which the determination was based. If correction is possible, the processing device 11 obtains from the database changed processing conditions for correcting the defect. If correction is not possible, the processing device 11 does not change the processing conditions.

[0071] The additive manufacturing apparatus 100 may repeatedly manufacture the same article. The processing conditions for manufacturing the next article may be changed based on the judgment results when manufacturing the previous article. For example, when the processing apparatus 11 judges that there is a defect when manufacturing the previous article, it changes the processing conditions at the position where the defect was judged when manufacturing the next article. This suppresses the occurrence of defects when manufacturing the next article.

[0072] FIG. 9 is a flowchart showing the operation of the monitoring system according to the embodiment. With reference to FIG. 9, the operation of the monitoring system 1 when changing the processing conditions will be described. As in the flowchart shown in FIG. 7, the collection device collects information during additive manufacturing (step S1). The processing device 11 acquires the information (step S2) and determines whether or not there is a defect (step S3). The processing device 11 determines whether or not there is a defect (step S11). If it is determined that there is a defect, the processing device 11 refers to the database and determines whether or not the defect can be corrected (step S12). If the defect can be corrected, the processing device 11 changes the processing conditions (step S13). This allows the defect that has occurred to be corrected. Or, the occurrence of the defect in the next article can be suppressed.

[0073] After it is determined in step S11 that no defect exists, after it is determined in step S12 that correction is impossible, or after step S13, the processing device 11 stores the result in the storage device 14 (step S14). Specifically, the processing device 11 stores the determination result, whether the defect can be corrected, the changed processing conditions, and the like for the area where the presence or absence of a defect has been determined. The processing device 11 determines whether the additive manufacturing is completed (step S15). If it is not completed, step S1 is executed again. Alternatively, step S2 and subsequent steps may be executed after information on each area during additive manufacturing is collected. In this case, steps S2 to S12 are repeated until processing based on each piece of information is completed. When the determination for each area is completed, the processing device 11 generates quality data (step S4).

[0074] The processing device 11 may determine the quality of the article based on the determination results of each region. For example, the quality data further includes information regarding the quality of the article.

[0075] FIG. 10 is a flowchart showing the operation of the monitoring system according to the embodiment. The processing device 11 may execute the process shown in Fig. 10 in step S4 of the flowchart shown in Fig. 7 or 9. The processing device 11 accesses the storage device 14 and refers to the judgment results of each area (step S41). The processing device 11 judges whether the presence of a defect has been judged in any area (step S42). If the presence of a defect has not been judged in any area, the processing device 11 judges the quality of the item to be excellent (step S43).

[0076] For example, the database contains a correspondence between information about defects and defect modes. If it is determined that a defect exists in any area, the processing device 11 accesses the database and compares information such as the number of defects, the positions of the defects, and the types of defects with the defect mode (step S44). For example, the database contains data indicating whether each defect mode is acceptable or not. The processing device 11 determines whether the obtained defect mode is acceptable (step S45). If the defect mode is acceptable, the processing device 11 determines the quality to be acceptable (step S46). If the defect mode is unacceptable, the processing device 11 determines the quality to be poor (step S47).

[0077] Excellent indicates that the quality is better than acceptable. Acceptable indicates that the quality is better than poor. Here, an example of classifying the quality into three grades has been described. The quality may be classified into four or more grades depending on the presence or absence of defects, the defect mode, etc.

[0078] The processing device 11 generates a report as the quality data (step S48). For example, the report includes the presence or absence of defects, the number of defects, the type of defects, the changed processing conditions, the defect mode, an image of the area where the defect is determined, and the quality. The processing device 11 displays the report on the display device 13 (step S49). Alternatively, the processing device 11 may output the report in a predetermined file format such as "Comma Separated Value (CSV)" and write it to a recording medium such as an SD card. The processing device 11 may transmit data to an external server using File Transfer Protocol (FTP) or the like, or may perform database communication and insert data into an external database server using Open Database Connectivity (ODBC) or the like.

[0079] FIG. 11 is a schematic diagram showing a hardware configuration. For example, the processing device 11 of the monitoring system 1 according to the embodiment is a computer, and includes a Read Only Memory (ROM) 11a, a Random Access Memory (RAM) 11b, a Central Processing Unit (CPU) 11c, and a Hard Disk Drive (HDD) 11d.

[0080] The ROM 11a stores a program for controlling the operation of the computer, including programs required for causing the computer to realize each of the above-mentioned processes.

[0081] The RAM 11b functions as a storage area in which the programs stored in the ROM 11a are loaded. The CPU 11c includes a processing circuit. The CPU 11c reads the control programs stored in the ROM 11a and controls the operation of the computer according to the control programs. The CPU 11c also loads various data obtained by the operation of the computer in the RAM 11b. The HDD 11d stores data required for reading and data obtained during the reading process. The HDD 11d functions as, for example, the storage device 14 shown in FIG. 2.

[0082] The processing device 11 may include an embedded multi media card (eMMC), a solid state drive (SSD), a solid state hybrid drive (SSHD), etc., instead of the HDD 11d. Each process and function of the processing device 11 may be realized by the cooperation of more computers.

[0083] The input device 12 includes at least one of a mouse, a keyboard, and a touch pad. The display device 13 includes at least one of a monitor and a projector. A device that functions as both the input device 12 and the display device 13, such as a touch panel, may be used.

[0084] According to the monitoring system, processing device, or monitoring method described above, the quality of an additively manufactured article can be more easily grasped. Also, a similar effect can be obtained by using a program for operating a computer as a processing device.

[0085] The various data processing operations described above may be recorded on a magnetic disk (such as a flexible disk or hard disk), an optical disk (such as a CD-ROM, CD-R, CD-RW, DVD-ROM, DVD±R, DVD±RW), a semiconductor memory, or other recording medium as a program that can be executed by a computer.

[0086] For example, data recorded on a recording medium can be read by a computer (or an embedded system). The recording medium may have any recording format (storage format). For example, the computer reads a program from the recording medium and causes a CPU to execute instructions described in the program based on the program. In the computer, the program may be acquired (or read) through a network.

[0087] Although some embodiments of the present invention have been illustrated above, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, substitutions, modifications, etc. can be made without departing from the gist of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are included in the scope of the invention and its equivalents described in the claims. In addition, the above-mentioned embodiments can be implemented in combination with each other. [Explanation of symbols]

[0088] 1: monitoring system, 2: additive manufacturing system, 11: processing device, 12: input device, 13: display device, 14: storage device, 21: imaging device, 22: temperature sensor, 23: lighting device, 100: additive manufacturing device, 101: control device, 110: first container, 111: first stage, 120: second container, 121: second stage, 130: coater, 140: irradiation device, 141: optical system, 150: laser light, 201: metal powder, 205: powder bed, 210: solidified portion, 211, 211a to 211c: beads, 220: molten pool, D1: first direction, D2: second direction, D3: third direction, Li1 to Li3: line segments

Claims

1. A collection device for collecting information of a solidified portion during additive manufacturing in which a metal powder is repeatedly melted and solidified to form a plurality of layers, the collection device including an imaging device, the information including a first image showing a first bead and a second bead included in the solidified portion, a molten molten pool, and a heat source; a processing device that acquires from the first image first data including one or more data selected from a width of the first bead immediately after solidification, a contour of the first bead, a surface shape of the first bead, a width of the second bead adjacent to the first bead, a contour of the second bead, a surface shape of the second bead, and a size of the heat source, determines the presence or absence of a defect in the solidified portion based on the first data, and generates quality data indicating the presence or absence of the defect; Equipped with a monitoring system.

2. 2. The monitoring system according to claim 1, wherein the processing device refers to a preset condition for the first data and judges the presence or absence of the defect by comparing the first data with the condition.

3. The monitoring system according to claim 1 or 2, wherein the processing device acquires the first data including an outline of the first bead and an outline of the heat source by inputting the first image into a first model.

4. The monitoring system according to claim 1 , wherein the processing device extracts differences between a plurality of the first images and determines the presence or absence of the defect in the solidified portion based on the differences.

5. the information further includes a second image of the powder bed after a new layer of the metal powder has been applied and before the metal powder is melted; The monitoring system according to claim 1 , wherein the processing device acquires a surface shape of the powder bed from the second image, and determines the presence or absence of the defect in the solidified portion based on the surface shape of the powder bed.

6. the information further includes a third image of the solidified portion after the metal powder has melted and solidified and before a new layer of the metal powder is applied; The monitoring system according to claim 1 , wherein the processing device acquires a surface shape of the solidified portion from the third image, and determines the presence or absence of the defect in the solidified portion based on the surface shape of the solidified portion.

7. 7. The monitoring system according to claim 1, wherein, when the processing device determines that there is a defect, the processing device adds the first image used for the determination to the quality data.

8. The monitoring system according to any one of claims 1 to 7, further comprising an illumination device for illuminating the coagulation area.

9. the collection device includes a temperature sensor; the information includes second data indicative of a temperature of the molten molten pool and a temperature of the solidified portion; 9. The monitoring system according to claim 1, wherein the processing device determines the presence or absence of the defect in the solidified portion based on the second data.

10. The monitoring system according to any one of claims 1 to 9, wherein the collection device collects the information on the coagulation portion as each of the plurality of layers is formed.

11. the collection device collects a plurality of the information during additive manufacturing; The processing device determines the presence or absence of the defect in a plurality of regions of the solidified portion, 11. The monitoring system according to claim 1, wherein the quality data includes the presence or absence of the defect and the location of the area including the defect.

12. The monitoring system according to any one of claims 1 to 11, wherein the processing device changes processing conditions during additive manufacturing based on the result of determining whether or not there is a defect.

13. A monitoring system according to any one of claims 1 to 12, An additive manufacturing device for performing additive manufacturing; Additive manufacturing system with.

Images