Quality analysis display device, additive manufacturing system, quality analysis display method, and quality analysis display program

Abstract

This quality analysis display device (4) comprises a processing log reading unit (17) that reads a processing log including data indicating the state of a workpiece during manufacturing of a molded article manufactured by additive manufacturing. The quality analysis display device (4) comprises a quality analysis unit (18) that analyzes, on the basis of the processing log, a quality reduction of a manufactured molded article for each of a plurality of quality items indicating a phenomenon that can occur in the molded article. The quality analysis display device (4) comprises a display unit (19) that displays an analysis result for each of the plurality of quality items.

Description

Quality analysis display device, additive manufacturing system, quality analysis display method, and quality analysis display program

[0001] The present disclosure relates to a quality analysis display device, an additive manufacturing system, a quality analysis display method, and a quality analysis display program that analyze the quality of a structure manufactured by additive manufacturing and display the analysis results.

[0002] Additive manufacturing (AM) is known as one of the methods for manufacturing three-dimensional objects. To enable the manufacturing of high-quality objects, it is important to analyze the quality of the object and use the analysis results to identify the causes of quality degradation.

[0003] Various phenomena that reduce the quality of objects manufactured by additive manufacturing can occur. One of the phenomena that can occur in objects is internal defects. Internal defects are gaps that form inside the object. Internal defects can reduce the mechanical strength of the object. Phenomena other than internal defects can also reduce the quality of objects.

[0004] Patent Document 1 discloses a data output device that outputs quality information indicating whether the quality of a molded object is acceptable or not, based on information acquired during the manufacture of the object. In the technology disclosed in Patent Document 1, the information acquired during the manufacture of the object includes image information acquired by photographing the layer being molded. The data output device disclosed in Patent Document 1 analyzes the quality of the layer being molded from the image information, and determines that the layer is of poor quality if a defect is found in the layer. The defect remains as an internal defect in the molded object after manufacture.

[0005] Japanese Patent Application Laid-Open No. 2021-165035

[0006] Although Patent Document 1 describes analyzing quality degradation due to internal defects based on image information, it does not mention a method for analyzing quality degradation due to phenomena other than internal defects. In other words, while the technology disclosed in Patent Document 1 makes it possible to analyze quality degradation due to internal defects, which are one of the phenomena that can occur in a molded object, it does not make it possible to analyze quality degradation due to each of multiple phenomena that can occur in a molded object. Therefore, the technology disclosed in Patent Document 1 has a problem in that it is difficult to analyze quality degradation due to each of multiple phenomena that can occur in a molded object.

[0007] The present disclosure has been made in view of the above, and aims to provide a quality analysis display device that is capable of analyzing quality degradation due to each of a plurality of phenomena that can occur in a shaped object.

[0008] In order to solve the above-mentioned problems and achieve the objectives, the quality analysis display device of the present disclosure includes a processing log reading unit that reads a processing log including data indicating the state of a workpiece during the production of a molded object manufactured by additive manufacturing, a quality analysis unit that analyzes quality degradation of the molded object based on the processing log for each of a plurality of quality items that indicate phenomena that may occur in the manufactured object, and a display unit that displays the analysis results for each of the plurality of quality items.

[0009] The quality analysis display device according to the present disclosure has the effect of being able to analyze quality degradation caused by each of a plurality of phenomena that can occur in a shaped object.

[0010] FIG. 1 is a diagram showing an example of the configuration of an additive manufacturing system according to embodiment 1. FIG. 2 is a diagram showing an example of the configuration of a modeling unit included in an additive manufacturing device of an additive manufacturing system according to embodiment 1. FIG. 3 is a flowchart showing an example of the operation procedure of an additive manufacturing system according to embodiment 1. FIG. 4 is a diagram showing an example of the display of a processing log in a quality analysis display device included in an additive manufacturing system according to embodiment 1. FIG. 5 is a diagram showing quality analysis by a quality analysis display device included in an additive manufacturing system according to embodiment 1. FIG. 6 is a diagram showing wall thickness reduction analyzed by a quality analysis display device included in an additive manufacturing system according to embodiment 1. FIG. 3 is a third diagram for explaining metal loss analyzed by the quality analysis display device of the additive manufacturing system according to embodiment 1; FIG. 4 is a diagram showing a first example of quality loss across two or more layers or two or more beads, analyzed by the quality analysis unit of the additive manufacturing system according to embodiment 1; FIG. 5 is a first diagram showing a second example of quality loss across two or more layers or two or more beads, analyzed by the quality analysis unit of the additive manufacturing system according to embodiment 1; FIG. 6 is a second diagram showing a second example of quality loss across two or more layers or two or more beads, analyzed by the quality analysis unit of the additive manufacturing system according to embodiment 1; FIG. 7 is a diagram showing an example of display of analysis results in the quality analysis display device of the additive manufacturing system according to embodiment 1;

[0011] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A quality analysis display device, an additive manufacturing system, a quality analysis display method, and a quality analysis display program according to embodiments will be described in detail below with reference to the accompanying drawings.

[0012] 1 is a diagram showing an example of the configuration of an additive manufacturing system 1 according to embodiment 1. The additive manufacturing system 1 includes an additive manufacturing device 2 that manufactures a model by additive manufacturing, a storage device 3 that stores information, and a quality analysis display device 4 that analyzes the quality of the model and displays the analysis results.

[0013] The additive manufacturing device 2 includes a modeling unit 11 that performs additive manufacturing of the object, a numerical control (NC) unit 12 that controls the modeling unit 11, a detection unit 13, a data analysis unit 14, and a processing log acquisition unit 15.

[0014] 2 is a diagram showing an example of the configuration of the modeling unit 11 included in the additive manufacturing apparatus 2 of the additive manufacturing system 1 according to embodiment 1. The modeling unit 11 is an apparatus that performs additive manufacturing using the Directed Energy Deposition (DED) method. In the DED method, a beam is irradiated onto a workpiece, and material is supplied to the irradiation position to melt the material and perform modeling.

[0015] The modeling unit 11 supplies material to the workpiece and produces a model by stacking beads formed from the material melted using a beam. The beam is a heat source that melts the material, such as a laser beam or an electron beam. The heat source is not limited to a beam and may be an arc. In the first embodiment, a case where the heat source is a laser beam is taken as an example. In the first embodiment, the material is a metal wire 31. The material is not limited to a wire 31 and may be a powder.

[0016] The manufacturing unit 11 forms a bead by irradiating the wire 31 and the workpiece with a laser beam while supplying the wire 31 to a position commanded by the NC unit 12. The bead is formed in a molten pool, which is a pool of molten metal formed by melting the workpiece and wire 31 through irradiation with the laser beam.

[0017] A substrate 32 is placed in the modeling unit 11. A layer is formed on the substrate 32 by arranging multiple beads. A model, which is a deposit of beads, is formed by stacking the layers. In this way, the modeling unit 11 manufactures a model by stacking beads. The substrate 32 is, for example, a plate material. The substrate 32 may be an object other than a plate material. The workpiece is an object to which molten material is added, and includes the substrate 32 and the model being modeled. The model is formed on the substrate 32.

[0018] The X-axis, Y-axis, and Z-axis are three axes that are perpendicular to each other. The X-axis and Y-axis are two horizontal axes. The Z-axis is a vertical axis. In each of the X-axis, Y-axis, and Z-axis directions, the direction indicated by the arrow is positive, and the direction opposite to the arrow is negative. The positive Z-direction is assumed to be the vertically upward direction. Hereinafter, it is assumed that a molded object is formed by stacking multiple layers in the positive Z-direction. Each of the multiple layers is assumed to be made up of multiple beads.

[0019] The modeling unit 11 includes a laser oscillator 21, an axis driver 22, a gas supply device 23, a material supply device 24, a processing head 25, and a stage 26. The substrate 32 is placed in the modeling unit 11 by being fixed to the stage 26.

[0020] A laser oscillator 21, which is a beam source, outputs a laser beam. The laser beam output by the laser oscillator 21 propagates through a fiber cable 30, which is an optical transmission path, and enters the processing head 25. An optical system such as a collimating optical system or a focusing optical system is disposed inside the processing head 25. The optical system is not shown in the figure. The laser oscillator 21, fiber cable 30, and processing head 25 constitute an irradiation unit that irradiates the workpiece with the laser beam.

[0021] The processing head 25 is provided with a beam nozzle through which the laser beam emitted from the processing head 25 toward the processing point passes, and a gas nozzle 29 that sprays shielding gas toward the processing point. The central axis of the beam nozzle coincides with the optical axis of the optical system. The central axis of the beam nozzle also coincides with the Z-axis. The center line of the laser beam irradiated onto the workpiece coincides with the Z-axis. The laser beam passes through the optical system inside the processing head 25 and exits from the processing head 25 through the beam nozzle. The processing point is the position on the workpiece where the laser beam is irradiated and the area where material is added. The shaping unit 11 moves the processing point along the movement path while adding molten material. The position of the processing point is the position where the heat source and material are supplied, and is located on the central axis of the beam nozzle.

[0022] The gas supply device 23 supplies shielding gas from a gas supply source to the gas nozzle 29. An example of the gas supply source is a gas cylinder. The gas supply source is connected to the gas nozzle 29 via piping. The gas supply source and piping are not shown. The gas supply device 23 can change the flow rate of the shielding gas based on a gas supply command from the NC unit 12. The injection of the shielding gas reduces oxidation of the material and the workpiece and cools the molded object. The shielding gas is preferably an inert gas such as argon gas.

[0023] The material supply device 24, which is a material supply unit, supplies the wire 31 toward the processing point. The material supply device 24 includes a material supply source 27 and a material supply nozzle 28. The material supply device 24 supplies the wire 31, which is unwound from the material supply source 27, to the processing point using the material supply nozzle 28. FIG. 2 shows an example of a side supply system in which the wire 31 is supplied from the material supply nozzle 28 located diagonally above the processing point. Instead of the side supply system, the material supply device 24 may also be a center supply system in which the wire 31 is supplied from the material supply nozzle 28 located directly above the processing point. The material supply device 24 is operated by a servo motor and can change the supply speed of the wire 31 based on a material supply command from the NC unit 12.

[0024] The axis drive device 22 moves the machining head 25 in the X-axis, Y-axis, and Z-axis directions based on a movement speed command from the NC unit 12. An example of the axis drive device 22 is a servo motor that moves the machining head 25 in the X-axis direction, a servo motor that moves the machining head 25 in the Y-axis direction, and a servo motor that moves the machining head 25 in the Z-axis direction. The servo motors are not shown. The positional relationship between the machining head 25, the material supply source 27 and material supply nozzle 28 that are the material supply device 24, and a height sensor 43 (described later) is fixed. As the machining head 25 moves, the material supply source 27, the material supply nozzle 28, and the height sensor 43 also move. By operating the servo motors, the modeling unit 11 can move the laser beam irradiation position, the wire 31 supply position, and the measurement position by the height sensor 43 to any position within the stroke range of the machining head 25.

[0025] The axis driving device 22 moves the machining head 25 in each of the X-axis direction, the Y-axis direction, and the Z-axis direction. That is, the axis driving device 22 causes the machining head 25 to perform linear motion in each of the three axes. The modeling unit 11 may be any device that moves the machining head 25 relative to the workpiece. The modeling unit 11 may also move the stage 26 relative to the machining head 25 in at least one of the X-axis direction, the Y-axis direction, and the Z-axis direction.

[0026] The modeling unit 11 includes a rotation mechanism that rotates the stage 26. The rotation mechanism is not shown. For example, the modeling unit 11 includes a rotation mechanism that rotates the stage 26 around the Z axis and a rotation mechanism that rotates the stage 26 around the X axis. The modeling unit 11 causes the stage 26 to perform rotational motion around each of the two axes. The modeling unit 11 changes the posture of the workpiece by causing the stage 26 to perform rotational motion. The modeling unit 11 can change the posture of the workpiece to a posture suitable for processing. Note that the modeling unit 11 may also include a rotation mechanism that rotates the stage 26 around the Y axis instead of the rotation mechanism that rotates the stage 26 around the X axis.

[0027] The detection unit 13 shown in Fig. 1 has various sensors that detect the state of the workpiece during the production of a molded object. The coaxial camera 41, the exterior camera 42, and the height sensor 43 shown in Fig. 2 are examples of sensors included in the detection unit 13. Each of these sensors included in the detection unit 13 outputs data resulting from detecting the state of the workpiece to the data analysis unit 14. Hereinafter, the data output by each sensor to the data analysis unit 14 will be referred to as raw data.

[0028] The coaxial camera 41 is installed on the central axis of the beam nozzle. The coaxial camera 41 captures an image of an area of ​​the workpiece including the processing point from vertically above. The coaxial camera 41 sends the captured image data to the data analysis unit 14.

[0029] The exterior cameras 42 are installed around the stage 26. The exterior cameras 42 photograph the exterior of the workpiece. The exterior cameras 42 send the photographed image data to the data analysis unit 14 shown in FIG. 1.

[0030] The height sensor 43 measures the height of the object. In the first embodiment, the height is the length in the Z-axis direction. In the first embodiment, the height sensor 43 is a laser displacement sensor. The height sensor 43 emits a laser beam toward the workpiece and receives the laser beam reflected by the workpiece. The height sensor 43 sends data of the received light waveform, which indicates the relationship between the intensity of the received laser beam and the position at which the laser beam is received, to the data analysis unit 14.

[0031] In the example described here, the raw data output by each sensor to data analysis unit 14 includes an image acquired by coaxial camera 41, an image acquired by exterior camera 42, and a received light waveform acquired by height sensor 43. Note that the raw data may include data other than these images and received light waveforms.

[0032] The data analysis unit 14 is realized, for example, by using a PC (Personal Computer). The data analysis unit 14 analyzes the raw data sent from each sensor to obtain measurement data representing the state of the workpiece. For example, the data analysis unit 14 measures the width of the molten pool, the center position of the molten pool, or the tip position of the wire 31 by analyzing images sent from the coaxial camera 41. The data analysis unit 14 measures the height of each bead by analyzing images sent from the external camera 42. The data analysis unit 14 measures the height of the molded object by analyzing the waveform of received light sent from the height sensor 43. The data analysis unit 14 outputs the measurement data to the NC unit 12. The data analysis unit 14 outputs the raw data acquired from each sensor to the machining log acquisition unit 15.

[0033] The NC unit 12 is realized by using, for example, a PC. The NC unit 12 controls the molding unit 11 in accordance with a processing program and processing conditions. The processing program describes movement commands for moving the processing head 25 along a predetermined path. The processing conditions include information necessary for bead formation, such as the laser output, which is the output of the laser beam from the laser oscillator 21, the movement speed, which is the speed at which the processing point is moved on the workpiece, the feed speed of the wire 31, and the gas flow rate, which is the flow rate of the shielding gas.

[0034] The NC unit 12 controls the axis drive device 22 in accordance with the machining program by outputting a position command corresponding to the machining program to the axis drive device 22. The axis drive device 22 moves the machining head 25 along a preset movement path in accordance with the position command. The NC unit 12 outputs a movement speed command to the axis drive device 22 in accordance with the machining conditions. The axis drive device 22 moves the machining head 25 at a movement speed in accordance with the movement speed command.

[0035] The NC unit 12 controls the laser oscillator 21 by outputting a laser output command to the laser oscillator 21 in accordance with the processing conditions. The laser oscillator 21 outputs a laser beam in accordance with the laser output command. The NC unit 12 controls the material supply device 24 by outputting a material supply command to the material supply device 24 in accordance with the processing conditions. The material supply device 24 supplies the wire 31 at a supply speed in accordance with the material supply command. The NC unit 12 controls the gas supply device 23 by outputting a gas supply command to the gas supply device 23 in accordance with the processing conditions. The gas supply device 23 supplies shielding gas at a gas flow rate in accordance with the gas supply command.

[0036] The NC unit 12 acquires various feedback values ​​by acquiring measurement data from the data analysis unit 14. The feedback values ​​acquired by the NC unit 12 include, for example, a feedback value of the axis position, which is the position of the machining head 25, a feedback value of the movement speed of the machining head 25, a feedback value of the laser output, and a feedback value of the feed speed of the wire 31. The NC unit 12 adjusts a position command based on the feedback value of the axis position. The NC unit 12 adjusts a movement speed command based on the feedback value of the movement speed. The NC unit 12 adjusts a laser output command based on the feedback value of the laser output. The NC unit 12 adjusts a material feed command based on the feedback value of the feed speed of the wire 31.

[0037] The NC unit 12 outputs various commands output to the modeling unit 11 and various feedback values ​​acquired from the data analysis unit 14 to the processing log acquisition unit 15. Hereinafter, the data output by the NC unit 12 to the processing log acquisition unit 15 will be referred to as an NC log. The NC log may include data other than these various commands and various feedback values.

[0038] The processing log acquisition unit 15 is realized, for example, by using a PC. The processing log acquisition unit 15 acquires raw data sent from the data analysis unit 14 and NC logs sent from the NC unit 12. Hereinafter, the raw data and NC logs acquired by the processing log acquisition unit 15 are referred to as processing logs. Of the processing logs, the raw data sent from the data analysis unit 14 and various feedback values ​​included in the NC log sent from the NC unit 12 can be considered data indicating the state of the workpiece during the manufacturing of the object by the modeling unit 11. Furthermore, of the processing logs, various commands included in the NC log sent from the NC unit 12 can be considered data used for control of additive manufacturing by the modeling unit 11. In other words, the processing log acquisition unit 15 acquires a processing log including data indicating the state of the workpiece during the manufacturing of the object manufactured by additive manufacturing and data used for control of additive manufacturing. The processing log acquisition unit 15 outputs the acquired processing log to the storage device 3.

[0039] The storage device 3 is realized, for example, by using a PC. The storage device 3 has a storage unit 16 that stores processing logs. Here, processing until the formation of all layers constituting the shaped object is completed is considered to be one processing session. In other words, the modeling unit 11 manufactures one shaped object through one processing session. The processing logs stored in the storage unit 16 are divided into folders for each processing session. "Processing log_0001", "Processing log_0002", etc. shown in FIG. 1 represent processing logs divided into folders. Each folder stores the processing log for one processing session. The processing logs stored in the folders are accumulated in the storage unit 16.

[0040] In the above description, it has been described that one folder stores the processing log for one processing operation, but this is not limited to this. For example, processing logs for each of the multiple layers constituting the object may be divided into folders. In this case, one folder stores the processing log for forming one layer. When one object is manufactured, the same number of folders as the number of layers constituting the object are formed in the storage unit 16, and processing logs for each layer are stored in each folder. Alternatively, one folder may store processing logs for forming two or more layers. In this way, the manner in which processing logs are divided into folders is arbitrary.

[0041] The quality analysis display device 4 includes a processing log reading unit 17, a quality analysis unit 18, and a display unit 19. The processing log reading unit 17 reads the processing log stored in the memory unit 16. That is, the processing log reading unit 17 reads the processing log including data indicating the state of the workpiece during the production of the shaped object produced by additive manufacturing and data used for control of the additive manufacturing. The processing log reading unit 17 outputs the read processing log to each of the quality analysis unit 18 and the display unit 19.

[0042] The quality analysis unit 18 analyzes quality degradation of the manufactured object for each of a plurality of quality items that indicate phenomena that may occur in the manufactured object, based on the processing log. The quality analysis unit 18 analyzes quality degradation of the manufactured object, based on the processing log input to the quality analysis unit 18.

[0043] In the first embodiment, the quality of the object refers to the relative merits of factors that determine the properties of the object. The properties of the object are mechanical properties or chemical properties of the object. The properties of the object may also include other properties that determine the quality of the product.

[0044] One of the multiple quality items is an internal defect in the molded object. An internal defect is a gap formed inside the molded object. Of the multiple quality items, quality items other than internal defects include, for example, the grain size of the crystals contained in the molded object, the composition distribution of the molded object, or wall thinning of the molded object. Coarsening of crystal grains or refinement of crystal grains affects the mechanical properties of the molded object. Uneven composition in the molded object affects the chemical properties of the molded object. Wall thinning of the molded object refers to a shortage of the outer shape of the molded object relative to the target shape. Wall thinning is a phenomenon that leads to a decrease in the mechanical strength of the molded object or a decrease in its value as a product.

[0045] The multiple quality items may include quality items other than those described here, such as whether or not a processed object is formed within the object, the expansion of the outer shape of the object relative to the target shape, the stress intensity factor of the object, or oxidation of the object.

[0046] The quality analysis unit 18 holds an analysis logic, which is logic for quality analysis, for each of the multiple quality items. The quality analysis unit 18 performs quality analysis for each of the multiple quality items using the analysis logic held in the quality analysis unit 18. For example, the quality analysis unit 18 holds one analysis logic for each quality item. The multiple quality items may include a quality item for which two or more analysis logics are held. For a quality item for which two or more analysis logics are held, the quality analysis unit 18 selects one of the two or more analysis logics and performs quality analysis for the quality item using the selected analysis logic. The analysis logic held in the quality analysis unit 18 may be updated as needed. The quality analysis unit 18 outputs the results of the quality degradation analysis to the display unit 19.

[0047] The display unit 19 receives the processing log from the processing log reading unit 17 and the analysis results from the quality analysis unit 18. The display unit 19 displays the data included in the processing log. The display unit 19 displays the analysis results for each of the multiple quality items based on the analysis results by the quality analysis unit 18.

[0048] Next, a description will be given of the operation procedure of the additive manufacturing system 1. Fig. 3 is a flowchart showing an example of the operation procedure of the additive manufacturing system 1 according to embodiment 1. Here, the description will mainly focus on the operation for analyzing quality degradation of a molded object and displaying the results of the quality degradation analysis.

[0049] In step S1, the modeling unit 11 starts manufacturing a model. When manufacturing of the model starts, the detection unit 13 detects the state of the workpiece and outputs raw data to the data analysis unit 14. The data analysis unit 14 analyzes the raw data and outputs measurement data to the NC unit 12. The data analysis unit 14 outputs the raw data to the processing log acquisition unit 15. The NC unit 12 outputs the NC log to the processing log acquisition unit 15.

[0050] The processing log acquisition unit 15 sends a processing log including the raw data sent from the data analysis unit 14 and the NC log sent from the NC unit 12 to the storage device 3. In step S2, the storage device 3 records the processing log sent from the processing log acquisition unit 15 to the storage device 3 in the storage unit 16. In step S3, the modeling unit 11 finishes manufacturing the modeled object.

[0051] In step S4, the processing log reading unit 17 reads the processing log. The processing log reading unit 17 outputs the processing log to each of the quality analysis unit 18 and the display unit 19. In step S5, the display unit 19 displays the data included in the processing log.

[0052] In step S6, the quality analysis unit 18 analyzes the quality degradation of the shaped object based on the processing log. For example, the quality analysis unit 18 performs the analysis when a user instructs the quality analysis. Here, the user is an operator who operates the quality analysis display device 4. The user instructs the quality analysis display device 4 to perform a quality analysis by performing an input operation on the quality analysis display device 4. The user also specifies, by performing an input operation on the quality analysis display device 4, a quality item among multiple quality items for which a quality degradation analysis is to be performed. The quality analysis unit 18 performs a quality degradation analysis for the specified quality item. The quality analysis unit 18 outputs the analysis result to the display unit 19.

[0053] In step S7, the display unit 19 displays the result of analyzing the quality degradation based on the analysis result from the quality analysis unit 18.

[0054] In step S8, the quality analysis unit 18 determines whether to change the quality item or the analysis logic and perform the analysis. The user can instruct the quality analysis display device 4 to change the quality item for which quality degradation is analyzed by inputting an instruction. If an instruction to change the quality item is given, the quality analysis unit 18 determines to change the quality item and perform the analysis. If the quality item for which quality degradation was analyzed in step S6 is a quality item for which two or more analysis logics are held, the user can instruct the quality analysis display device 4 to change the analysis logic by inputting an instruction. If an instruction to change the analysis logic is given, the quality analysis unit 18 determines to change the analysis logic and perform the analysis.

[0055] If the analysis is to be performed by changing the quality items or the analysis logic (Step S8, Yes), the quality analysis display device 4 returns the procedure to Step S6. The quality analysis unit 18 performs analysis on the changed quality items or analysis using the changed analysis logic. On the other hand, if the analysis is not to be performed by changing the quality items or the analysis logic (Step S8, No), the quality analysis display device 4 proceeds to Step S9.

[0056] In step S9, the quality analysis unit 18 determines whether to change the processing log and perform the analysis. The user can instruct the quality analysis display device 4 to change the processing log and perform the analysis. At that time, the user may specify the processing log to be analyzed and instruct the change to the specified processing log. When instructed to change the processing log and perform the analysis, the quality analysis unit 18 determines that the processing log will be changed and the analysis will be performed.

[0057] If the processing log is changed and analysis is performed (step S9, Yes), the quality analysis display device 4 returns the procedure to step S4. The processing log reading unit 17 reads a processing log different from the processing log read in the previous step S4. If a processing log is specified by the user, the processing log reading unit 17 reads the specified processing log.

[0058] On the other hand, if the processing log is not to be changed and analyzed (step S9, No), the quality analysis display device 4 ends the operation according to the procedure shown in FIG.

[0059] Next, the machining log will be described in detail. The machining log includes raw data and an NC log. The raw data includes, for example, an image of the area including the machining point, an image of the appearance of the workpiece, or a received light waveform. Hereinafter, the image of the area including the machining point will be referred to as a molten pool image. The image of the appearance of the workpiece will be referred to as an appearance image. The molten pool image is captured by the coaxial camera 41. The appearance image is captured by the appearance camera 42. The received light waveform is generated by the height sensor 43.

[0060] The coaxial camera 41 captures molten pool images at a predetermined cycle. Each molten pool image captured by the coaxial camera 41 is assigned an image number indicating the order in which it was captured. The exterior camera 42 captures exterior images at a predetermined cycle. Each exterior image captured by the exterior camera 42 is assigned an image number. The height sensor 43 outputs received light waveforms at a predetermined cycle. Each received light waveform output by the height sensor 43 is assigned a received light waveform number indicating the order in which it was output. The machining log acquisition unit 15 periodically acquires molten pool images each assigned an image number, exterior images each assigned an image number, and received light waveforms each assigned a received light waveform number. Note that if the raw data contains data other than the data described here, the data included in the raw data is assigned a number indicating its order in time series, similar to the image number or received light waveform number. Hereinafter, the number indicating its order in time series will be referred to as a time series number.

[0061] The NC log includes a position command, an axis position feedback value, a laser output command, a laser output feedback value, a material supply command, or a feedback value of the supply speed of the wire 31. The NC log also includes the scanning amount in the Z-axis direction, the scanning amount in the X-axis direction and the Y-axis direction, data on the tip position of the wire 31, the width of the molten pool, the center position of the molten pool, the height of the object, or the bead height. The bead height is the height of one bead.

[0062] The processing log acquisition unit 15 acquires a count value by counting the timing at which the NC log is acquired from the NC unit 12. Hereinafter, this count value will be referred to as the NC count value. The NC log includes the NC count value. The NC log also includes a layer number and a workpiece number. The layer number is a number assigned to each of multiple layers in a shaped object, and the workpiece number is a number assigned to each of multiple shaped objects manufactured by the additive manufacturing device 2.

[0063] In the first embodiment, the processing log includes a processing program and a three-dimensional model of the object. The three-dimensional model of the object is a model that represents the target shape of the object to be manufactured by the additive manufacturing apparatus 2. The processing program and the three-dimensional model are sent from the NC unit 12 to the processing log acquisition unit 15. That is, the processing log acquisition unit 15 acquires the processing program and the three-dimensional model from the NC unit 12. The processing log acquisition unit 15 may also acquire at least one of the processing program and the three-dimensional model from the data analysis unit 14.

[0064] Since the NC log contains NC count values ​​and the raw data contains time series numbers, the NC log and the raw data are recorded in a state in which they can be synchronized with each other in the storage device 3. Note that the data included in the processing log is not limited to the data described here and may be any data.

[0065] The processing log reading unit 17 reads the processing logs stored in the memory unit 16. The processing log reading unit 17 reads the processing logs for each folder. When a processing log for one processing session is stored in one folder, the processing log reading unit 17 reads the processing log for each processing session. When a processing log for one layer is stored in one folder, the processing log reading unit 17 reads the processing log for each layer. When processing logs for two or more layers are stored in one folder, the processing log reading unit 17 reads the processing log for each of the two or more layers.

[0066] The user specifies the processing log to be displayed by the display unit 19 by inputting an input operation to the quality analysis display device 4. The processing log reading unit 17 reads the processing log specified by the user.

[0067] In the above description, the processing log reading unit 17 reads processing logs stored in one folder. However, the processing log reading unit 17 may also read processing logs stored in multiple folders. For example, if a processing log for one processing session is stored in one folder and the user specifies processing logs for multiple processing sessions, the processing log reading unit 17 reads processing logs stored in multiple folders. Therefore, the display unit 19 may display the processing log for one processing session or the processing logs for multiple processing sessions. The quality analysis unit 18 may analyze quality degradation based on the processing log for one processing session or the processing logs for multiple processing sessions. In addition, even if a processing log for one layer is stored in one folder or if processing logs for two or more layers are stored in one folder, the processing log reading unit 17 may also read processing logs stored in multiple folders.

[0068] The processing log reading unit 17 links the NC log included in the read processing log with the raw data included in the read processing log. The processing log reading unit 17 links the NC log with the raw data based on the NC count value included in the NC log and the time series number included in the raw data.

[0069] Fig. 4 is a first diagram for explaining the processing log read by the processing log reading unit 17 of the additive manufacturing system 1 according to embodiment 1. Fig. 5 is a second diagram for explaining the processing log read by the processing log reading unit 17 of the additive manufacturing system 1 according to embodiment 1.

[0070] Figure 4 shows an example of the NC log and raw data included in the machining log. In Figure 4, the NC count value, the wire 31 feed speed, and the weld pool width are NC log items. In Figure 4, the image number of the weld pool image, the image number of the appearance image, and the received light waveform number are raw data items. These items shown in Figure 4 are a portion of all the items in the machining log.

[0071] Here, the NC log is assumed to be acquired by the processing log acquisition unit 15 approximately every 20 milliseconds. In this case, the NC count value is incremented by 1 approximately every 20 milliseconds. The frame rate of the coaxial camera 41 is assumed to be approximately 50 fps (frames per second). The frame rate of the exterior camera 42 is assumed to be approximately 25 fps. The height sensor 43 is assumed to output a received light waveform approximately 50 times per second.

[0072] In the table shown in Fig. 4, the NC count values ​​are arranged in ascending order in the NC count value column. In the table shown in Fig. 4, the wire 31 feed speed column represents the feedback value of the wire 31 feed speed at the NC count value listed in the NC count value column. In the table shown in Fig. 4, the weld pool width column represents the weld pool width at the NC count value listed in the NC count value column.

[0073] In the table shown in Fig. 4, the column for "image number of molten pool image" indicates the image number of the molten pool image synchronized with the NC log at the NC count value listed in the column for "NC count value." As shown in Fig. 4, each NC count value listed in the column for "NC count value" is associated with the image number of the molten pool image acquired at the timing of the NC count value. The association between the NC count value and the image number of the molten pool image is determined based on the cycle at which the NC log is acquired and the frame rate of the molten pool image.

[0074] In the table shown in Fig. 4, the column of image numbers for appearance images indicates the image numbers of appearance images synchronized with the NC logs at the NC count values ​​listed in the column of NC count values. As shown in Fig. 4, each NC count value listed in the column of NC count values ​​is associated with the image number of the appearance image acquired at the timing of the NC count value. The association between the NC count value and the image number of the appearance image is determined based on the cycle at which the NC logs are acquired and the frame rate of the appearance images.

[0075] In the table shown in Fig. 4, the column "Received Light Waveform Number" indicates the received light waveform number of the received light waveform synchronized with the NC log at the NC count value listed in the column "NC Count Value." As shown in Fig. 4, each NC count value listed in the column "NC Count Value" is associated with the received light waveform number of the received light waveform acquired at the timing of the NC count value. The association between the NC count value and the received light waveform number is determined based on the cycle at which the NC log is acquired and the cycle at which the received light waveform is output.

[0076] 5 shows examples of a molten pool image file, an appearance image file, and a received light waveform file. Here, the appearance images are assumed to be taken by each of the two appearance cameras 42. The two appearance cameras 42 take images of the appearance of the workpiece from different positions. The image taken by one of the two appearance cameras 42 is referred to as the first appearance image. The image taken by the other of the two appearance cameras 42 is referred to as the second appearance image.

[0077] In the memory unit 16, in the folder storing the machining log, a folder storing files of molten pool images, a folder storing data of appearance images, and a folder storing data of received light waveforms are further created. In Figure 5, the molten pool image folder is a folder storing files of molten pool images. The first appearance image folder is a folder storing first appearance images. The second appearance image folder is a folder storing second appearance images. The received light waveform folder is a folder storing files of received light waveforms.

[0078] In Figure 5, files are schematically represented by rectangles with file names written on them. In Figure 5, "im_1.bmp", "im_2.bmp", ... in the molten pool image folder are file names of molten pool image files. The file names of molten pool image files include a number representing the image number of the molten pool image. The file name of the first appearance image file includes a number representing the image number of the first appearance image. The file name of the second appearance image file includes a number representing the image number of the second appearance image. The file name of the received light waveform folder files includes a number representing the received light waveform number of the received light waveform.

[0079] As an example, as shown in FIG. 4, assume that the value indicating the wire 31 feed speed is "AA" and the value indicating the weld pool width is "BB" for an NC count value of "7." The wire 31 feed speed "AA" and the weld pool width "BB" are data included in the NC log for the NC count value of "7." The NC count value of "7" is also associated with the image number "7" of the weld pool image, the image number "4" of the appearance image, and the received light waveform number "7." In the table shown in FIG. 4, the row for the NC count value of "7" that is hatched with diagonal lines shows these values ​​and numbers associated with the NC count value of "7."

[0080] Based on this correspondence, the NC data with an NC count value of 7 is associated with "im_7.bmp" in the molten pool image folder, "im_4.bmp" in the first appearance image folder, "im_4.bmp" in the second appearance image folder, and "hgt_7.BIN" in the received light waveform folder. In Figure 5, diagonal hatching indicates files associated with the NC data with an NC count value of 7.

[0081] 6 is a diagram showing an example of a display of a processing log in the quality analysis display device 4 of the additive manufacturing system 1 according to embodiment 1. FIG. 6 shows an example of a screen 50 displayed by the display unit 19 shown in FIG. 1. The screen 50 has an image display unit 51 that displays an image included in the processing log, a graph display unit 52 that displays data included in the processing log in the form of a graph, and a numeric display unit 53 that displays data included in the processing log in the form of numerical values. The screen 50 also has a time operation unit 54 that accepts an operation to specify the current time on the display, and a processing log selection unit 55 that accepts an operation to select a processing log to be displayed on the screen 50.

[0082] 6, the image display section 51 is divided into four areas. The user can select an image to be displayed in each area of ​​the image display section 51. For example, each area of ​​the image display section 51 displays an image selected from a molten pool image, a first appearance image, a second appearance image, a received light waveform, and a machining progress image.

[0083] The machining progress image is an image that shows the progress of machining by the molding unit 11. The machining progress image displays a model 56 that represents the workpiece being machined, and an object 57 that represents the machining point on the workpiece. As an example, the model 56 represents the shape of the molded object that is reproduced based on the outer circumferential position of the molten pool and the height of the bead.

[0084] The display unit 19 determines the position of the machining point on the workpiece based on the feedback value of the axis position in the machining log. The display unit 19 displays an object 57 at a position corresponding to the determined position in the model 56 displayed in the machining progress image. The form of the object 57 is arbitrary.

[0085] In each area of ​​the image display unit 51, an image at a time specified by an operation on the time operation unit 54 is displayed. The number of areas in which images are displayed in the image display unit 51 is not limited to four and may be any number.

[0086] The graph display unit 52 displays a graph representing data for an item selected by the user from among multiple items included in the processing log. The graph display unit 52 displays any number of graphs. An operation for selecting data to be displayed on the graph display unit 52 is received, for example, by the graph display unit 52. The horizontal axis of each graph displayed on the graph display unit 52 represents time. The vertical axis of each graph displayed on the graph display unit 52 represents a numerical value indicated by the data. The graph display unit 52 displays an object 58 representing a time specified by an operation on the time operation unit 54. The form of the object 58 is arbitrary.

[0087] The numerical value display unit 53 has a display field 62 in which the numerical values ​​of data for an item selected by the user from among multiple items included in the processing log are displayed. Numeric values ​​for any number of items are displayed in the display field 62. In the example shown in Fig. 6, the display field 62 displays the name of the item, the unit of the numerical value, and the numerical value. The display field 62 displays the numerical value of each piece of data at a time specified by an operation on the time operation unit 54.

[0088] The time operation unit 54 has a bar 59 for moving the current time on the display on a time axis representing the period during which the processing log was acquired, and a button unit 60 for accepting operations to operate the bar 59. The position of the bar 59 on the time axis represents the current time on the display. The button unit 60 has, for example, a play button, a stop button, a fast-forward button, a fast-rewind button, a frame-by-frame button, and a frame-by-frame button. The play button accepts an operation to advance the current time on the display. The stop button accepts an operation to stop the current time on the display. The fast-forward button accepts an operation to fast-forward the current time on the display. The fast-rewind button accepts an operation to fast-rewind the current time on the display. The frame-by-frame button accepts an operation to alternately advance and stop the current time on the display. The frame-by-frame button accepts an operation to alternately rewind and stop the current time on the display. The current time on the display can be changed by the user operating each button. The current time on the display can also be changed by the user dragging the bar 59 .

[0089] As the current time on the display changes, the image on the image display unit 51 is switched to an image of the current time on the display at any time. As the current time on the display changes, the object 58 moves on the horizontal axis of each graph on the graph display unit 52. As the current time on the display changes, the numerical value displayed on the numerical value display unit 53 is switched to the numerical value of the current time on the display at any time.

[0090] The user can check the synchronized raw data and NC log on the screen 50 displayed by the display unit 19. This allows the user to simultaneously check the state of the workpiece during the production of the object and the data used for control of additive manufacturing.

[0091] The display unit 19 can synchronize and display any two or more selected images from the molten pool image, the appearance image, the received light waveform, and the machining progress image on the image display unit 51. By being able to simultaneously check two or more images from the same time, the user can easily understand the state of the workpiece during the production of the molded object. Furthermore, by displaying the object 57 together with the model 56 in the machining progress image, the user can easily understand the progress of machining at the current time on the display.

[0092] The screen 50 has a quality analysis button 61 that accepts a quality analysis instruction from the user. When the quality analysis button 61 is pressed by a user operation, the quality analysis unit 18 analyzes the quality degradation of the molded object based on the processing log. The display unit 19 displays the results of the analysis by the quality analysis unit 18. As an example, the display unit 19 displays the results of the analysis by the quality analysis unit 18 on the screen 50. An example of how the results of the analysis by the quality analysis unit 18 are displayed will be described later.

[0093] For example, the quality analysis unit 18 analyzes quality degradation for each of a plurality of quality items when the quality analysis button 61 is pressed. Alternatively, the quality analysis unit 18 may analyze quality degradation for only the quality items selected by the user when the quality analysis button 61 is pressed. In this case, the user can arbitrarily select the quality items to be analyzed and check the analysis results for the selected quality items.

[0094] Next, details of the quality analysis by the quality analysis unit 18 will be described. FIG. 7 is a diagram for explaining quality analysis by the quality analysis display device 4 of the additive manufacturing system 1 according to the first embodiment. FIG. 7 shows an example of information input to the quality analysis unit 18, an example of intermediate data which is information generated inside the quality analysis unit 18, and an example of information output from the quality analysis unit 18. In the first embodiment, the intermediate data can be said to be data that first appears during the process of determining quality information from the information input to the quality analysis unit 18. The quality analysis display device 4 may or may not hold the intermediate data.

[0095] 7, the processing log is information input to the quality analysis unit 18. Data items included in the processing log are listed in Fig. 7. Note that the data items included in the processing log are not limited to those shown in Fig. 7.

[0096] 7, each of the machining program and the three-dimensional model is information input to the quality analysis unit 18. By inputting the machining program and the three-dimensional model to the quality analysis unit 18, the quality analysis unit 18 can analyze the quality of the shape of the shaped object with high accuracy.

[0097] When a quality analysis instruction is given by the user, the processing log, the processing program, and the 3D model of the object are input to the quality analysis unit 18. The quality analysis unit 18 obtains intermediate data, an example of which is shown in Fig. 7, based on the information input to the quality analysis unit 18. The quality analysis unit 18 outputs quality information, which is the result of analyzing the quality degradation of the object, based on the intermediate data.

[0098] In this way, the quality analysis unit 18 obtains intermediate data indicating the cause of quality degradation for each quality item based on the processing log, the processing program, and the three-dimensional model. The quality analysis unit 18 outputs the analysis result for each quality item by calculating the intermediate data.

[0099] The quality analysis unit 18 obtains data indicating the results of detecting phenomena that cause quality degradation as intermediate data. In the example shown in Fig. 7, the intermediate data includes data indicating the levels of drops, stubs, wire rubbing, bead gaps, dripping, thermal distortion, heat accumulation, and control deviation. Each of drops, stubs, wire rubbing, bead gaps, dripping, thermal distortion, heat accumulation, and control deviation is considered to be a phenomenon that causes quality degradation.

[0100] A drop is a mass of molten material that occurs when the molten material remains at the tip of the wire 31. A drop occurs when the wire 31 melts at a position away from the workpiece. A drop can cause phenomena such as thinning or internal defects, which are a reduction in the accuracy of the shape of the molded object. For example, the quality analysis unit 18 calculates a drop level that represents the size of the drop by determining the dimensions of the molten material that remains at the tip of the wire 31. The quality analysis unit 18 may calculate the drop level by determining the distance between the tip of the wire 31 and the center of the laser beam. The quality analysis unit 18 may calculate the drop level by determining the gap between the tip of the wire 31 and the workpiece.

[0101] A stub is a phenomenon in which the tip of the wire 31 collides with the workpiece while it is still unmelted during molding. The stub causes an internal defect. For example, the quality analysis unit 18 calculates a stub level, which indicates the strength of the stub, based on the positional relationship between the melting position and the processing surface of the workpiece where the bead is formed. The melting position is defined as the position where the temperature of the wire 31 reaches its melting point. The quality analysis unit 18 calculates the melting position based on the feed speed of the wire 31 and the laser output.

[0102] Wire rubbing is a phenomenon in which the unmelted wire 31 rubs against the bead, leaving a mark on the bead. Wire rubbing can cause internal defects. For example, the quality analysis unit 18 calculates the wire rubbing level, which indicates the strength of wire rubbing, based on the relationship between the bead height and the penetration point. The penetration point is defined as the position where the wire 31 penetrates the laser beam irradiation range.

[0103] Bead gaps are a phenomenon in which gaps occur between adjacent beads due to the bead width being narrower than expected. Bead gaps can cause internal defects. For example, the quality analysis unit 18 calculates a bead gap level that represents the size of the bead gap based on the result of comparing the bead width with a threshold value. The threshold value to be compared with the bead width is calculated based on the pitch at which the beads are arranged side by side on the processed surface and the width of the overlapping portions of the beads.

[0104] Dripping is a phenomenon in which a molded object before solidification is deformed due to the influence of gravity or surface tension during molding. Dripping causes thinning of the molded object. For example, the quality analysis unit 18 calculates the dripping level, which indicates the size of the dripping, by performing a flow analysis based on the temperature of the molded object and the physical properties of the material, such as the viscosity or melting point.

[0105] Thermal strain is a phenomenon in which a molded object is distorted due to a change in temperature of the object. Thermal strain causes thickness reduction. For example, the quality analysis unit 18 calculates a thermal strain level that represents the magnitude of thermal strain by performing a thermal strain analysis based on the temperature of the object and the physical properties of the material, such as the thermal expansion coefficient or Young's modulus.

[0106] Heat accumulation is a phenomenon in which the heat input to the object exceeds the cooling rate of the object, causing the object to be maintained at a high temperature and resulting in a slower cooling rate. Heat accumulation can cause coarsening of crystal grains in the object or uneven composition in the object. Heat accumulation can also cause oxidation in parts of the object that are outside the area where the shielding gas is sprayed. For example, the quality analysis unit 18 calculates the heat accumulation level, which indicates the level of heat accumulation, based on the temperature of the object and the physical properties of the material, such as the laser beam absorptivity, thermal conductivity, heat transfer coefficient, or radiant heat.

[0107] The control error is a phenomenon such as an overshoot in the control of the axis drive device 22 or a control delay in the axis drive device 22. The control error causes an error in the width of the formed bead from the target width. Therefore, the control error causes phenomena such as thinning or internal defects, which are a reduction in the accuracy of the shape of the molded object. For example, the quality analysis unit 18 calculates a control error level that indicates the magnitude of the control error based on the bead width, the bead center position, the scanning amount on the X-axis and Y-axis, the feedback values ​​of the axis positions on the X-axis and Y-axis, or the deviation of the processing point from the target position.

[0108] The quality analysis unit 18 associates the detected level of each of the multiple phenomena that cause quality degradation with a position on the shaped object. For example, in the intermediate data shown in Fig. 7, "(position, drop level)" represents drop level data associated with a position.

[0109] The data included in the intermediate data is not limited to the data about the above phenomena, but may also include data about phenomena such as incorrect height measurement or incorrect width measurement of the molten pool.

[0110] A height measurement error is a phenomenon in which an error occurs in the measurement of the height of the object by the height sensor 43. For example, a height measurement error occurs when multiple peaks appear in the received light waveform output from the height sensor 43. The NC unit 12 calculates the Z-axis scanning amount based on the measurement results from the height sensor 43. Therefore, a height measurement error reduces the accuracy of the Z-axis scanning amount, resulting in a drop or stub. The measurement results from the height sensor 43 are used to control the height correction of the object. A height measurement error reduces the accuracy of the height correction of the object, resulting in wall thinning. For example, the quality analysis unit 18 determines whether a height measurement error exists based on the number of peaks that appear in the received light waveform.

[0111] Incorrect weld pool width measurement refers to an error in the weld pool width measurement by the data analysis unit 14. For example, an incorrect weld pool width measurement can occur when the weld pool image is unclear. The NC unit 12 controls the laser output and bead width based on the weld pool width measurement results. Therefore, incorrect weld pool width measurement can result in a bead width that is narrower than expected, causing bead gaps or metal loss. Alternatively, incorrect weld pool width measurement can result in a bead width that is wider than expected, causing a decrease in the shape accuracy of the molded object. For example, the quality analysis unit 18 determines whether or not there is an incorrect weld pool width measurement based on the weld pool width measurement results and the weld pool image.

[0112] In the above description, the detected levels of each of the plurality of phenomena in the intermediate data obtained by the quality analysis unit 18 are linked to their positions in the shaped object, but this is not limiting. In the intermediate data, the detected levels of each of the plurality of phenomena may be linked to layer numbers assigned to layers in the shaped object, or may be linked to workpiece numbers assigned to the shaped object.

[0113] 7, the quality information is information output from the quality analysis unit 18. The quality information includes quality level data indicating the level of quality degradation for each of a plurality of quality items. In the example shown in FIG. 7, the quality level data included in the quality information is quality level data for each of the quality items: internal defects, crystal grain size, composition distribution, wall thinning, and oxidation.

[0114] The quality analysis unit 18 associates the quality level detected for each of the multiple quality items with a position on the object. For example, in the quality information shown in Fig. 7, "(position, internal defect level)" represents data on the internal defect level associated with the position. Note that the data included in the quality information is not limited to the data on the quality items described here.

[0115] The internal defect level is a quality level for internal defects. The internal defect level is, for example, a quantitative value of the size of voids, which are internal defects. The internal defect level may be the maximum, average, or median value of the void size, or the surface area of ​​the voids.

[0116] The crystal grain size level is a quality level for the crystal grain size. The crystal grain size level is, for example, a quantitative value of the crystal grain size. The crystal grain size level may be the maximum value, average value, or median value of the crystal grain size. For example, the quality analysis unit 18 estimates the crystal grain size level based on the relationship between the temperature and time of the molded object and the physical property values ​​of the material. The quality analysis unit 18 may estimate the crystal grain size level by simulation using a method such as the phase field method.

[0117] The composition distribution level is a quality level of the composition distribution, and the grain size level is, for example, data representing the composition of the grain boundary or data representing the presence or absence of precipitates.

[0118] The metal loss level is a quality level of the metal loss. For example, the quality analysis unit 18 calculates the metal loss level as a quantitative value of the difference between the shape of the object obtained by additive manufacturing and the target shape of the object. The quality analysis unit 18 reproduces the shape of the object obtained by additive manufacturing based on the outer circumferential position of the molten pool and the height of the bead. Data indicating the position of the molten pool on the outer shape and data indicating the height of the bead are included in the processing log. The position of the molten pool on the outer shape can be calculated from a molten pool image. The height of the bead can be calculated based on the results of measuring the height of each of the multiple layers of the object using the height sensor 43. The target shape of the object is represented by a three-dimensional model input to the quality analysis unit 18. In this way, the quality analysis unit 18 calculates the metal loss level based on the processing log.

[0119] Figure 8 is a first diagram for explaining the wall-reduction analyzed by the quality analysis display device 4 included in the additive manufacturing system 1 according to embodiment 1. Figure 9 is a second diagram for explaining the wall-reduction analyzed by the quality analysis display device 4 included in the additive manufacturing system 1 according to embodiment 1. Figure 10 is a third diagram for explaining the wall-reduction analyzed by the quality analysis display device 4 included in the additive manufacturing system 1 according to embodiment 1.

[0120] A shape 71 shown by a solid line in Fig. 8 is an example of the shape of a molded object obtained by additive manufacturing. A shape 72 shown by a dashed line in Fig. 8 is an example of the target shape of a molded object. In Fig. 8, the shapes 71 and 72 are superimposed on each other.

[0121] FIG. 9 shows an XY cross section of shape 71, which is a molded object obtained by additive manufacturing, and an XY cross section of shape 72, which is a target shape. In FIG. 9, each of the circles represents the outline of the molten pool when a layer of shape 71 including the cross section shown in FIG. 9 is formed. The curved arrow in FIG. 9 represents the direction in which the processing point moves. Compared to shape 72, the portion of shape 71 on the negative X side is shifted in the negative Y direction. This shift is caused by the heat distribution in the molded object or the surface tension generated in the molded object. Furthermore, suppose that the shift cannot be fully corrected due to a control delay when the molded object is formed, and the shift remains in the molded object.

[0122] The left part of Fig. 10 shows a YZ cross section of four beads 74 constituting a molded object of shape 71, which is a molded object obtained by additive manufacturing. The right part of Fig. 10 shows a YZ cross section of four beads 74 constituting a molded object of shape 72, which is a target shape. The height of each bead 74 in shape 72 represents the target height of the bead 74. In the example shown in Fig. 10, the height of each bead 74 in shape 71 is lower than the target height of each bead 74. Such insufficient height of the bead 74 can be caused by, for example, a control delay. The deviation described with reference to Fig. 9 or the insufficient height described with reference to Fig. 10 can cause a reduction in thickness of the shape 71.

[0123] In Figure 8, a portion 73 of the shape 72 near the tip in the positive Z direction is insufficient in the shape 71. In other words, thinning of the shape 71 has occurred. The quality analysis unit 18 can obtain the size of the portion 73 as the thinning level. In this way, the quality analysis unit 18 can calculate the thinning level by comparing the shape of the object with the target shape. The quality analysis display device 4 may visually indicate the thinning level by displaying the shape of the object obtained by additive manufacturing and the target shape superimposed on each other on the display unit 19, as shown in Figure 8.

[0124] As described above, the quality analysis unit 18 calculates the metal-reduction level based on the processing log. Therefore, the quality analysis unit 18 can accurately calculate the metal-reduction level even if two-dimensional or three-dimensional measurements of the shape of the object are not performed. By using the shape of the object obtained by additive manufacturing, the quality analysis unit 18 can estimate the metal-reduction level taking into account dripping or thermal strain. The user may estimate the air cut or machining allowance in cutting from the metal-reduction level estimation result by the quality analysis unit 18. By using the shape of the object obtained by additive manufacturing to estimate the metal-reduction level, the air cut or machining allowance in cutting can be accurately estimated.

[0125] In the above description, the metal-reduction level is the difference between the shape of the object obtained by additive manufacturing and the target shape of the object, but this is not limited to this. The metal-reduction level may also be the difference between the shape of the object obtained by additive manufacturing and a shape calculated based on the movement path. The shape calculated based on the movement path is a shape calculated based on the target value of the bead width, the bead height, and the movement path. The shape calculated based on the movement path can also be said to be a shape obtained by thickening the movement path based on the target value of the bead width and the bead height.

[0126] 7 , the oxidation level refers to a quality level of oxidation of the object. The oxidation level is, for example, a quantitative value of the oxidation concentration of the object. For example, the quality analysis unit 18 estimates the oxidation concentration of the object based on the relationship between the temperature and time of the object, the oxygen concentration of the shielding gas, the amount of shielding gas retained at each position on the object, and the oxidation temperature, which is a physical property value of the material. The amount of shielding gas retained is calculated by multiplying the flow rate of the shielding gas by the retention time of the shielding gas.

[0127] The quality analysis unit 18 may output, as the quality level, a score obtained by scoring or the like for each of the multiple quality items. The method for obtaining the score indicating the quality level is arbitrary. For example, the quality analysis unit 18 obtains the score by comparing a predetermined threshold value with a quantitative value or the like. For each of the multiple quality items, the threshold value may be changed depending on the material or the use of the object. The quality analysis unit 18 may output, as the quality level, the results of analyzing signs of quality deterioration.

[0128] In the above description, the quality level required by the quality analysis unit 18 is linked to a position in the object, but this is not limiting. The quality level required by the quality analysis unit 18 may be linked to a layer number assigned to a layer in the object, or may be linked to a workpiece number assigned to the object.

[0129] The quality analysis unit 18 may derive quality information using any method. Four methods will be described below as examples of methods for deriving quality information using the quality analysis unit 18. Note that each of the methods described here also includes a method for deriving intermediate data.

[0130] In the first method of deriving quality information, the results of a simulation or experiment carried out in advance are stored in a table in the quality analysis display device 4. Then, the quality analysis unit 18 derives the quality information using the results of the simulation or experiment read from the table.

[0131] In the second method for deriving quality information, a calculation for detecting a phenomenon that causes quality degradation from the processing log is formulated using the results of a simulation or experiment conducted in advance, and the quality analysis unit 18 then derives the quality information using the calculation formula obtained by the formulation.

[0132] In the third method for deriving the quality information, the quality analysis unit 18 uses the current processing log itself, which is the processing log acquired when deriving the quality information, to simulate a phenomenon that causes a quality degradation. The quality analysis unit 18 derives the quality information by simulating a phenomenon that causes a quality degradation.

[0133] In a fourth method for deriving quality information, the quality analysis unit 18 derives the quality information by machine learning of the processing log. Any conventionally known machine learning method can be used for the machine learning of the processing log.

[0134] By deriving quality information in this manner in the quality analysis unit 18, the quality analysis display device 4 can shorten the time required for quality analysis or improve the accuracy of the quality analysis. Furthermore, by using the processing log recorded in the storage device 3 for quality analysis, quality analysis based on data over a longer period of time becomes possible compared to real-time analysis. This enables the quality analysis display device 4 to predict quality degradation with high accuracy. Note that real-time analysis refers to analyzing the acquired processing log when the processing log is acquired.

[0135] In the first method, the simulation results or experimental results, which are information stored in the table, may be updated as appropriate. In the second method, the calculation formula may be updated as appropriate. In the third method, the simulation method may be updated as appropriate. In the fourth method, the trained model used for machine learning may be updated as appropriate. These updates in each of the first to fourth methods correspond to the update of the analysis logic described above.

[0136] When the analysis logic is updated, the quality analysis unit 18 may execute quality analysis based on the updated analysis logic. This enables the quality analysis display device 4 to predict quality degradation with high accuracy. Furthermore, the quality analysis display device 4 can execute quality analysis by repeatedly changing parameters in the quality analysis by the quality analysis unit 18. Such parameters are, for example, parameters that indicate the calculation pitch when a simulation is performed.

[0137] As described above, the quality analysis display device 4 analyzes deterioration in the quality of the molded object using the processing log recorded in the storage device 3. The quality analysis display device 4 can analyze the overall quality of the molded object without using methods such as destructive testing. The quality analysis display device 4 can also automatically perform 100% inspection of the molded objects manufactured by the additive manufacturing apparatus 2. Furthermore, compared to radiographic inspection using X-ray CT (Computed Tomography) or inspection using ultrasonic flaw detection, the analysis method using the quality analysis display device 4 has the advantage of not imposing any restrictions on the shape or material of the molded object to be analyzed.

[0138] The processing log is recorded in the storage device 3, and the processing log read from the storage device 3 is used for analysis, so that the quality analysis unit 18 can analyze quality degradation of the shaped object based on the processing log for any period. For example, the quality analysis unit 18 may analyze quality degradation based on the processing logs for multiple unit periods, with the cycle at which the processing log is acquired by the processing log acquisition unit 15 being defined as the unit period.

[0139] The quality analysis display device 4 may perform a re-analysis by reading an already analyzed processing log from the storage device 3. In this case, the quality analysis unit 18 may analyze the processing log using an analysis logic different from the analysis logic used in the previous analysis. This allows the quality analysis display device 4 to perform an analysis with higher accuracy.

[0140] As described above, the quality analysis unit 18 can obtain intermediate data indicating the cause of quality degradation for each of a plurality of quality items and output quality information that is the result of analyzing the quality degradation of the shaped object based on the intermediate data. In this case, the quality analysis unit 18 can reduce the amount of processing log data to be input compared to when the quality information is obtained directly from the input. Furthermore, the quality analysis unit 18 can obtain more accurate quality information compared to when the quality information is obtained directly from the input. After obtaining the quality information, the user can easily check the cause of the quality degradation.

[0141] In the above, the additive manufacturing system 1 stores the processing log in the storage unit 16 of the storage device 3. The additive manufacturing system 1 may also store intermediate data calculated based on the processing log, etc., in the storage unit 16. The additive manufacturing system 1 may also store only the intermediate data without storing the processing log. When the additive manufacturing system 1 stores only the intermediate data, the data capacity of the storage unit 16 can be reduced compared to when the additive manufacturing system 1 stores the processing log. Furthermore, the additive manufacturing system 1 can shorten the analysis time in quality analysis after the intermediate data has been calculated, since it does not need to recalculate the intermediate data. The additive manufacturing system 1 enables efficient quality analysis by reducing analysis time, making it possible to obtain analysis results of the desired accuracy through efficient analysis in a short amount of time.

[0142] If the detection unit 13 does not include a thermometer, the quality analysis unit 18 can analyze the heat of the formed object by calculating the heat input amount of the formed object based on data included in the processing log, such as the laser output and the heat absorption rate of the material. If the detection unit 13 includes a thermometer that measures the temperature of the formed object, the quality analysis unit 18 can analyze the heat of the formed object using the temperature value measured by the thermometer.

[0143] The quality analysis unit 18 may analyze quality degradation based on a processing log for each layer constituting the object. The quality analysis unit 18 may analyze quality degradation in two or more layers adjacent to each other in the Z-axis direction based on processing logs for the two or more layers. In this case, the quality analysis unit 18 detects quality degradation spanning two or more layers from the processing logs when each of the two or more adjacent layers among the multiple layers was formed.

[0144] The quality analysis unit 18 may analyze quality degradation based on the processing log for each bead constituting a layer. Here, each of the multiple layers constituting the object is assumed to be composed of multiple beads arranged in the Y-axis direction. The multiple layers are stacked in the Z-axis direction. The quality analysis unit 18 may analyze quality degradation in two or more beads adjacent to each other in the Z-axis direction based on the processing log for the two or more beads. Alternatively, the quality analysis unit 18 may analyze quality degradation in two or more beads adjacent to each other in the Y-axis direction based on the processing log for the two or more beads. In this case, the quality analysis unit 18 detects quality degradation spanning two or more beads from the processing logs when each of the two or more adjacent beads among the multiple beads was formed.

[0145] Here, a specific example of quality degradation across two or more layers or two or more beads will be described. Figure 11 is a diagram showing a first example of quality degradation across two or more layers or two or more beads analyzed by the quality analysis unit 18 of the additive manufacturing system 1 according to the first embodiment.

[0146] 11, four layers 75-1, 75-2, 75-3, and 75-4 are layers that constitute the object. The four layers 75-1, 75-2, 75-3, and 75-4 are stacked in the positive Z direction in the order of layer 75-1, layer 75-2, layer 75-3, and layer 75-4. Each of the four layers 75-1, 75-2, 75-3, and 75-4 includes two beads 76 that are adjacent to each other in the Y-axis direction.

[0147] 11, a thinned portion 77 occurs in each of the two layers 75-2 and 75-3. Because the two layers 75-2 and 75-3 are stacked in the Z-axis direction, the thinned portions 77 of the two layers 75-2 and 75-3 are connected to each other in the Z-axis direction. In other words, the shaped object has a thinned portion that spans the two layers 75-2 and 75-3.

[0148] By using the processing log read from the storage device 3 for analysis, the quality analysis unit 18 can analyze the thinning that spans two or more beads adjacent to each other in the Y-axis direction. This analysis allows the user to easily understand that a larger thinning has occurred compared to the thinning that is limited to one layer. In this way, the quality analysis display device 4 allows the user to easily understand the nature of the quality degradation.

[0149] Figure 12 is a first diagram showing a second example of quality degradation spanning two or more layers or two or more beads, analyzed by the quality analysis unit 18 included in the additive manufacturing system 1 according to embodiment 1. Figure 13 is a second diagram showing a second example of quality degradation spanning two or more layers or two or more beads, analyzed by the quality analysis unit 18 included in the additive manufacturing system 1 according to embodiment 1.

[0150] Each of the three layers 78-1, 78-2, and 78-3 shown in Fig. 12 constitutes a model. The three layers 78-1, 78-2, and 78-3 are stacked in the positive Z direction in the order of layer 78-1, layer 78-2, and layer 78-3, as shown in Fig. 13. As shown in Fig. 12, each of the three layers 78-1, 78-2, and 78-3 includes two beads 79 adjacent to each other in the Y-axis direction.

[0151] As shown in Fig. 12, an internal defect 80 spanning two beads 79 has occurred in the layer 78-1. Furthermore, an internal defect 80 spanning two beads has occurred in the layer 78-2. As shown in Fig. 13, because the two layers 78-1 and 78-2 are stacked in the Z-axis direction, the internal defects 80 of the two layers 78-1 and 78-2 are connected to each other in the Z-axis direction. In other words, the object has an internal defect 80 spanning two layers 78-1 and 78-2.

[0152] By using the processing log read from the storage device 3 for analysis, the quality analysis unit 18 can analyze internal defects 80 that span two or more layers adjacent to each other in the Y-axis direction. Through such analysis, the user can easily understand that a larger internal defect 80 has occurred compared to an internal defect 80 that is limited to one layer. In this way, the quality analysis display device 4 allows the user to easily understand the nature of quality degradation.

[0153] FIG. 14 is a diagram showing a third example of quality degradation spanning two or more layers or two or more beads, analyzed by the quality analysis unit 18 included in the additive manufacturing system 1 according to the first embodiment. Each of the four layers 81-1, 81-2, 81-3, and 81-4 shown in FIG. 14 constitutes a model. The four layers 81-1, 81-2, 81-3, and 81-4 are stacked in the positive Z direction in the order of layer 81-1, layer 81-2, layer 81-3, and layer 81-4. Three crystal grains 82 are generated in the four layers 81-1, 81-2, 81-3, and 81-4. Each crystal grain 82 spans the four layers 81-1, 81-2, 81-3, and 81-4.

[0154] 14 , crystal grains 82 may grow across two or more layers. By using the processing log read from the storage device 3 for analysis, the quality analysis unit 18 analyzes the growth of crystal grains 82 in two or more layers based on the thermal histories of the two or more layers. Through such analysis, the user can easily grasp the presence of crystal grains 82 that have grown across two or more layers. In this way, the quality analysis display device 4 allows the user to easily grasp the nature of quality degradation.

[0155] Next, an example of the display of the results of the analysis by the quality analysis unit 18 will be described. Fig. 15 is a diagram showing an example of the display of the analysis results in the quality analysis display device 4 of the additive manufacturing system 1 according to the first embodiment. Fig. 15 shows one area of ​​the image display unit 51 on the screen 50 shown in Fig. 6. In the example described here, the display unit 19 displays the results of the analysis of quality degradation in one area of ​​the image display unit 51. This area is the area where the processing progress image is displayed.

[0156] The display unit 19 accepts an operation on the screen 50 to select a quality item from among the multiple quality items for which the analysis results are to be displayed. The portion of the screen 50 that accepts the operation is not shown. In the example shown in FIG. 15 , the display unit 19 displays the analysis results for the selected quality item by adding an object 64 at a position where a quality degradation for the selected quality item has been discovered. That is, the display unit 19 displays the analysis results by displaying the object 64, which indicates the level of quality degradation analyzed by the quality analysis unit 18, together with the outer shape of the molded object. For example, the outer shape of the molded object displayed on the display unit 19 is the shape of the molded object reproduced based on the outer circumferential position of the molten pool and the height of the bead.

[0157] Whether or not a quality degradation has been found is determined, for example, by the quality analysis unit 18 based on the quality level. The display unit 19 displays the analysis result of the quality degradation by displaying the outline of the model and the object 64. This enables the quality analysis display device 4 to allow the user to easily understand the results of the analysis of the quality degradation. The user can easily confirm from the display on the display unit 19 whether or not a model of the desired quality has been manufactured. Note that the form of the object 64 is arbitrary.

[0158] Note that the display of the results of the quality degradation analysis is not limited to showing the positions where the quality degradation was found. For example, the display unit 19 may display a model representing the object and color-code parts of the model where the quality degradation was found, thereby displaying the results of the quality degradation analysis. The display unit 19 may display the results of the quality degradation analysis by displaying the movement path of the processing point and color-code parts of the movement path where the quality degradation was found.

[0159] The display unit 19 may display the results of the analysis of quality degradation by displaying a graph showing the relationship between the position on the object and the quality level. The display unit 19 may display the results of the analysis of quality degradation by displaying a value indicating the quality level at the current time on the display. The display unit 19 may also display the positions where quality degradation has been discovered by a method other than the method described here.

[0160] The user can check the machining log when the part with reduced quality was formed from the various displays on the screen 50 when the quality degradation is displayed. The user can check whether there is an abnormality in the raw data or NC data when the part with reduced quality was formed on the graph display unit 52 or the numerical display unit 53. The user can check whether there is an abnormality in the molten pool image, appearance image, machining progress image, or received light waveform on the image display unit 51 when the part with reduced quality was formed.

[0161] The quality analysis display device 4 may create correction guidelines for the processing conditions, movement path, or shape of portions of the object whose quality level does not meet a predetermined standard. The quality analysis display device 4 may present the created correction guidelines to the user by displaying them on the display unit 19. The quality analysis display device 4 may also output the correction guidelines by a method other than display. This allows the user to easily improve the quality of the object by referring to the correction guidelines.

[0162] The quality analysis display device 4 may calculate the efficiency of modeling when forming the object. The display unit 19 may also display the calculation results of the modeling efficiency when displaying the results of analyzing the quality degradation. For example, the quality analysis display device 4 determines whether the retraction operation of the machining head 25 is excessive by comparing the shape of the object with the trajectory of the retraction operation of the machining head 25. The retraction operation is an operation in which the machining head 25 moves in a direction away from the workpiece from a state in which the wire 31 is in contact with the workpiece. It can be said that the more excessive the retraction operation, the lower the modeling efficiency.

[0163] The display unit 19 may display the calculation result of the modeling efficiency by color-coding the portion of the trajectory of the retraction operation that is determined to be excessive. This allows the user to easily understand the modeling efficiency along with the analysis result of the quality degradation.

[0164] Next, a hardware configuration for realizing the quality analysis display device 4 will be described. Fig. 16 is a diagram showing an example of a hardware configuration for realizing the quality analysis display device 4 according to the first embodiment. The quality analysis display device 4 is realized by a computer system including a communication device 91, a processing circuit 92, an input device 93, and a display device 94. The processing circuit 92 includes a processor 95 and a memory 96. The processing circuit 92 is a circuit on which the processor 95 executes software.

[0165] 1 are realized by software, firmware, or a combination of software and firmware. The software or firmware is written as a program and stored in memory 96. In the processing circuit 92, the processor 95 reads and executes the program stored in memory 96, thereby realizing the processing functions of the quality analysis display device 4. That is, the processing circuit 92 includes a memory 96 for storing a quality analysis display program, which is a program that results in the processing of the quality analysis display device 4. The quality analysis display program stored in memory 96 can also be said to cause a computer to execute the procedures and methods of the quality analysis display device 4.

[0166] The processor 95 is a CPU (Central Processing Unit), a central processing unit, a processing unit, an arithmetic unit, a microprocessor, a microcomputer, a processor, or a DSP (Digital Signal Processor). The memory 96 is, for example, a non-volatile or volatile semiconductor memory such as a RAM (Random Access Memory), a ROM (Read Only Memory), a flash memory, an EPROM (Erasable Programmable Read Only Memory), or an EEPROM (Electrically Erasable Programmable Read Only Memory), a magnetic disk, a flexible disk, an optical disk, a compact disk, a minidisk, or a DVD (Digital Versatile Disc).

[0167] The communication device 91 communicates with devices external to the quality analysis display device 4. The input device 93 is a device that is operated by a user to input information. The input device 93 includes, for example, a keyboard, a mouse, a keypad, or a touch panel. The display device 94 is a device that displays information. The display device 94 is, for example, an LCD (Liquid Crystal Display) or an organic EL (Electro-Luminescence) display. The display function of the display unit 19 is realized by the display device 94.

[0168] The quality analysis display device 4 may include an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The quality analysis display program may be provided by being stored on a recording medium such as a CD (Compact Disc)-ROM or a DVD-ROM. The quality analysis display program may also be stored in a computer connected to a network such as the Internet and provided by being downloaded via the network such as the Internet. The quality analysis display program may also be provided or distributed via a network such as the Internet.

[0169] In the first embodiment, the quality analysis display device 4 is realized by one device. However, the quality analysis display device 4 may be realized using two or more devices. The two or more devices are communicatively connected to each other. Each of the two or more devices has, for example, the same configuration as the communication device 91 and the processing circuit 92. The two or more devices include a device having the same configuration as the input device 93 and the display device 94. The two or more devices may include a cloud server. The cloud server is a server built in a cloud environment including computer resources provided by a cloud service platform. For example, the quality analysis unit 18 may be realized using the cloud server. Using the cloud server to realize the quality analysis unit 18 makes it easier to update the analysis logic.

[0170] Each of the NC unit 12, data analysis unit 14, and processing log acquisition unit 15 that make up the additive manufacturing apparatus 2 is realized by, for example, a computer system having a configuration similar to that of the communication device 91 and processing circuit 92. At least one of the NC unit 12, data analysis unit 14, and processing log acquisition unit 15 may include an integrated circuit such as an ASIC or FPGA.

[0171] In the above description, the additive manufacturing system 1 stores the processing log in the storage device 3 external to the quality analysis display device 4. The additive manufacturing system 1 may be configured to provide a storage unit 16 inside the quality analysis display device 4, and store the processing log in the storage unit 16 inside the quality analysis display device 4. The additive manufacturing system 1 may also be configured to save intermediate data in the storage unit 16 inside the quality analysis display device 4.

[0172] According to the first embodiment, the quality analysis display device 4 includes a processing log reading unit 17 that reads a processing log including data indicating the state of the workpiece during the production of a molded object manufactured by additive manufacturing, a quality analysis unit 18 that analyzes quality degradation of the manufactured object for each of a plurality of quality items that indicate phenomena that may occur in the manufactured object based on the processing log, and a display unit 19 that displays the analysis results for each of the plurality of quality items. This allows the quality analysis display device 4 to analyze quality degradation due to each of a plurality of phenomena that may occur in the molded object. Furthermore, the quality analysis display device 4 can display the results of the analysis of quality degradation due to each of the plurality of phenomena.

[0173] The multiple quality items also include one or more of: internal defects, which are gaps formed inside the object; grain size of crystals contained in the object; composition distribution of the object; and wall thinning, which is a deficiency in the outer shape of the object relative to the target shape of the object. This allows the quality analysis display device 4 to analyze quality degradation for a phenomenon that is one or more of internal defects, grain size of crystals, composition distribution, and wall thinning, and display the analysis results of the quality degradation for that phenomenon.

[0174] Furthermore, for a shaped object formed by stacking multiple layers, the quality analysis unit 18 detects quality degradation across two or more layers from the processing logs when two or more adjacent layers among the multiple layers were formed. This allows the quality analysis display device 4 to present the analysis results of quality degradation across two or more layers to the user.

[0175] Furthermore, for a shaped object formed by arranging a plurality of beads, the quality analysis unit 18 detects quality degradation spanning two or more beads from the processing logs when two or more adjacent beads among the plurality of beads are formed. This enables the quality analysis display device 4 to present the analysis results of quality degradation spanning two or more beads to the user.

[0176] Furthermore, the quality analysis unit 18 obtains intermediate data indicating the cause of quality degradation for each quality item based on the processing log, and outputs an analysis result for each quality item by calculating the intermediate data. This allows the quality analysis display device 4 to analyze quality degradation for each quality item based on the processing log consisting of a small amount of data. Furthermore, the quality analysis display device 4 can obtain highly accurate analysis results. After obtaining an analysis result indicating quality degradation, the quality analysis display device 4 can allow the user to easily confirm the cause of the quality degradation.

[0177] The display unit 19 also displays the analysis results by displaying an object 64, which indicates the level of quality degradation analyzed by the quality analysis unit 18, together with the outline of the shaped object. In this way, the quality analysis display device 4 allows the user to easily understand the results of the analysis of quality degradation.

[0178] The configurations described in the above embodiments are examples of the contents of the present disclosure. The configurations of the embodiments can be combined with other known technologies. Part of the configurations of the embodiments can be omitted or modified without departing from the gist of the present disclosure.

[0179] 1 Additive manufacturing system, 2 Additive manufacturing device, 3 Storage device, 4 Quality analysis display device, 11 Modeling unit, 12 NC unit, 13 Detection unit, 14 Data analysis unit, 15 Processing log acquisition unit, 16 Storage unit, 17 Processing log reading unit, 18 Quality analysis unit, 19 Display unit, 21 Laser oscillator, 22 Axis drive unit, 23 Gas supply unit, 24 Material supply unit, 25 Processing head, 26 Stage, 27 Material supply source, 28 Material supply nozzle, 29 Gas nozzle, 30 Fiber cable, 31 Wire, 32 Base material, 41 Coaxial camera, 42 Appearance camera, 43 Height sensor, 50 Screen, 51 Image display unit, 52 Graph display unit, 53 Numerical display unit, 54 Time operation unit, 55 Processing log selection unit, 56 Model, 57, 58, 64 Object, 59 Bar, 60 Button unit, 61 Quality analysis button, 62 display field, 71, 72 shape, 73 part, 74, 76, 79 bead, 75-1, 75-2, 75-3, 75-4, 78-1, 78-2, 78-3, 81-1, 81-2, 81-3, 81-4 layer, 77 thinning part, 80 internal defect, 82 crystal grain, 91 communication device, 92 processing circuit, 93 input device, 94 display device, 95 processor, 96 memory.

Claims

1. A quality analysis display device comprising: a processing log reading unit that reads a processing log containing data indicating the state of a workpiece during the manufacture of an object manufactured by additive manufacturing; a quality analysis unit that analyzes quality degradation of the manufactured object based on the processing log for each of a plurality of quality items that indicate phenomena that may occur in the manufactured object; and a display unit that displays the analysis results for each of the plurality of quality items.

2. The quality analysis display device described in claim 1, characterized in that the multiple quality items include one or more of internal defects, which are gaps formed inside the object, the grain size of crystals contained in the object, the composition distribution of the object, and thinning, which is a deficiency in the outer shape of the object compared to the target shape of the object.

3. The quality analysis display device according to claim 1 or 2, characterized in that the quality analysis unit detects quality degradation across two or more layers of the object formed by stacking multiple layers from the processing log when each of two or more adjacent layers among the multiple layers is formed.

4. The quality analysis display device according to claim 1 or 2, characterized in that the quality analysis unit detects quality degradation across two or more beads from the processing log when each of two or more adjacent beads among the multiple beads is formed for the object formed by arranging multiple beads.

5. A quality analysis display device as described in any one of claims 1 to 4, characterized in that the quality analysis unit obtains intermediate data indicating the causes of quality degradation for each of the quality items based on the processing log, and outputs the analysis results for each of the quality items by calculating the intermediate data.

6. A quality analysis display device according to any one of claims 1 to 5, characterized in that the display unit displays the analysis results by displaying an object representing the level of quality degradation analyzed by the quality analysis unit together with the outer shape of the object.

7. An additive manufacturing system comprising: an additive manufacturing device that manufactures a molded object by additive manufacturing; a storage device that stores a processing log, which is a data history showing the state of the molded object when manufactured by the additive manufacturing device; and a quality analysis display device that analyzes the quality of the molded object based on the processing log read from the storage device and displays the analysis results, wherein the quality analysis display device has: a processing log reading unit that reads the processing log stored in the storage device; a quality analysis unit that analyzes quality degradation of the molded object based on the processing log for each of a plurality of quality items that show phenomena that appear in the manufactured molded object; and a display unit that displays the analysis results for each of the plurality of quality items.

8. A quality analysis and display method for analyzing the quality of an object manufactured by additive manufacturing and displaying the analysis results using a computer, the quality analysis and display method comprising the steps of: reading a processing log, which is a data history showing the state of the object manufactured by additive manufacturing at the time of manufacturing; analyzing quality deterioration of the object based on the processing log for each of a plurality of quality items showing phenomena that appear in the manufactured object; and displaying the analysis results for each of the plurality of quality items.

9. A quality analysis display program that causes a computer to execute the steps of: reading a processing log, which is a data history showing the state of an object manufactured by additive manufacturing at the time of manufacture; analyzing quality deterioration of the object based on the processing log for each of a plurality of quality items that show phenomena that appear in the manufactured object; and displaying the analysis results for each of the plurality of quality items.

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