JP7593180B2 - DATA OUTPUT APPARATUS, THREE-DIMENSIONAL PRODUCTION SYSTEM AND DATA OUTPUT METHOD - Google Patents

Description

The present invention relates to three-dimensional modeling, and more specifically to a data output device, a three-dimensional modeling system, and a data output method.

In recent years, three-dimensional modeling devices have become known as devices that can model three-dimensional objects without using a mold or the like. For example, International Publication No. 2017/163432 (Patent Document 1) discloses a technology for estimating the quality of a model. However, this technology is limited to estimating the quality during modeling, and does not take into consideration quality assurance of the completed model (three-dimensional model).

The present disclosure aims to provide a data output device, a three-dimensional modeling system, and a data output method capable of outputting quality information of a three-dimensional object.

In view of the above, the present disclosure provides a data output device having the following characteristics. The data output device includes an acquisition means for acquiring specified information during three-dimensional modeling. The data output device includes an output means for outputting quality information of a three-dimensional object obtained by three-dimensional modeling based on the specified information.

The above configuration makes it possible to output quality information about a three-dimensional object.

1 is a diagram showing a schematic configuration of an entire three-dimensional object forming system according to a first embodiment. FIG. 1 is a diagram showing a system configuration of a three-dimensional modeling system according to a first embodiment. 2A to 2C are diagrams for explaining the relationship between three-dimensional model data, slice data, and a tool path in the three-dimensional object forming apparatus according to the first embodiment. FIG. 2 is a diagram showing a hardware configuration of a controller included in the three-dimensional object forming apparatus according to the first embodiment. FIG. 2 is a diagram illustrating a configuration around a nozzle included in the three-dimensional object forming apparatus according to the first embodiment. FIG. 2 is a functional block diagram showing a more detailed configuration of a controller included in the 3D object forming apparatus according to the first embodiment. 4 is a flowchart showing an overall flow of a modeling process executed in the three-dimensional modeling system according to the first embodiment. 6 is a flowchart showing a process of performing modeling while acquiring quality data, which is executed by the three-dimensional modeling apparatus according to the first embodiment. 4 is a diagram illustrating an example of a data structure of a control code processed by the three-dimensional object forming apparatus according to the first embodiment; 5 is a view illustrating an example of a data structure of quality data recorded by the three-dimensional object forming apparatus according to the first embodiment; FIG. 13 is a diagram illustrating a data structure of quality data recorded by a three-dimensional modeling apparatus according to another embodiment. FIG. 13 is a diagram illustrating a data structure of quality data recorded by a three-dimensional object forming apparatus according to still another embodiment. FIG. 13 is a diagram illustrating a configuration around a nozzle included in a three-dimensional object forming apparatus according to a second embodiment. 13 is a flowchart showing a process of performing modeling while acquiring quality data, which is executed by the three-dimensional modeling apparatus according to the second embodiment. 13 is a diagram illustrating an example of a data structure of quality data recorded by the three-dimensional object forming apparatus according to the second embodiment; 13A to 13C are views for explaining an analysis process based on image information, which is performed in the three-dimensional object forming apparatus according to the second embodiment. FIG. 13 is a diagram showing a system configuration of a three-dimensional modeling system according to a third embodiment. 13 is a flowchart showing a part of a process of performing modeling while acquiring quality data, which is executed by the three-dimensional modeling apparatus according to the third embodiment. FIG. 13 is a diagram showing a schematic configuration of the entire three-dimensional modeling system according to a fourth embodiment. FIG. 13 is a diagram showing a system configuration of a three-dimensional modeling system according to a fourth embodiment. 13 is a flowchart showing a process of acquiring information on a display screen of a peripheral device as quality data in a three-dimensional modeling system according to a fourth embodiment. 13A to 13C are views for explaining a process of extracting setting information from a display image on a display unit in the three-dimensional modeling system according to the fourth embodiment. 13A and 13B are views for explaining a process of comparing extracted setting information with a numerical range in the three-dimensional object forming system according to the fourth embodiment. 13 is a flowchart showing a process of comparing setting information and apparatus status information with range information in a three-dimensional modeling system according to a fourth embodiment. 13 is a flowchart showing another process of acquiring information on the display screen of a peripheral device as quality data in the three-dimensional modeling system according to the fourth embodiment. 13A to 13C are views for explaining a process of storing and discarding extracted setting information in the three-dimensional object forming system according to the fourth embodiment. FIG. 13 is a diagram showing a schematic configuration of the entire three-dimensional modeling system according to the fifth embodiment.

The following describes the present invention using a specific embodiment, but the present invention is not limited to the embodiment described below. In addition, in each of the figures referred to below, the same reference numerals are used for common elements, and their description will be omitted as appropriate.

Figure 1 is a diagram showing the overall schematic configuration of a three-dimensional modeling system 100 in the first embodiment. In the following explanation, a modeling device using the Fused Filament Fabrication (FFF) method will be mainly described, but the present invention is not limited to this, and in other embodiments, the present invention can be applied to other modeling methods such as photolithography, powder sintering additive manufacturing, and binder jetting. In the following explanation, for ease of explanation, the height direction of the modeled object will be the Z-axis direction, and the plane perpendicular to the Z-axis will be the XY plane.

As shown in FIG. 1A, the three-dimensional modeling system 100 includes a three-dimensional modeling device 110 that models a three-dimensional object as a three-dimensional modeling means. The three-dimensional modeling device 110 receives data for modeling a desired three-dimensional object from, for example, an information processing device 150, and models the three-dimensional object based on the data. The three-dimensional modeling device 110 has a mechanism for discharging a material (hereinafter referred to as modeling material) for generating a three-dimensional object at a specified position. The information processing device 150 can also operate as a control device that controls the processing executed by the three-dimensional modeling device 110. On the information processing device 150, software operates that has a function of interpreting a three-dimensional model representing a desired three-dimensional object, changing the orientation and arrangement coordinates of the three-dimensional model, and generating a discharging position of the modeling material. Note that the function of the information processing device 150 may be incorporated into the three-dimensional modeling device 110.

In the FFF method, a thin resin filament in a reel shape as the modeling material is sent to a nozzle by an extruder, melted by heat from a heater and turned into a liquid, and the modeling material is extruded in thread form from the high-temperature nozzle of the head 112. As shown in FIG. 1B, the modeling layer 102 is formed on the XY plane by discharging the modeling material from the nozzle onto the modeling plate 114 while moving the head 112 parallel to the XY plane. A line drawing is drawn on the same plane, and the extruded material cools and hardens on the modeling plate 114 to form one modeling layer of a three-dimensional object. That layer is modeled. When the first modeling layer is modeled, the modeling plate 114 is lowered by the height of one layer (layer pitch) in the direction along the Z axis. After that, the head 112 is driven in the same way as the first layer, and the second modeling layer is modeled. The 3D modeling device 110 repeats these operations to stack modeling layers and form the final 3D object. Note that, although the configuration in which the head 112 moves in the XY plane and the modeling plate 114 moves in the Z-axis direction has been described as an example, the above-described configuration does not limit this embodiment, and other configurations may also be used.

Figure 2 shows the system configuration of the three-dimensional modeling system 100 in the first embodiment. The information processing device 150 is configured as, for example, a personal computer, on which the slicer software 252 runs.

Three-dimensional model data 202 is input to the slicer software 252. The three-dimensional model data 202 is data that represents a three-dimensional shape in a predetermined expression format, such as, but not limited to, the STL (Standard Triangulated Language) format. The slicer software 252 reads the three-dimensional model data 202, slices the three-dimensional model in the Z-axis direction (height direction, the same as the Z-axis direction during modeling), creates slice data, and outputs control data 204 that represents a tool path, which is the trajectory of the nozzle discharging modeling material, for each slice data.

Figure 3 illustrates the relationship between the 3D model data, slice data, and tool path in the 3D modeling device 110 of the first embodiment.

The slicer software 252 slices the three-dimensional model 302 represented by the three-dimensional model data 300 into small slices in the height (Z-axis) direction, and generates slice data 312 that extracts the cross-sectional shape of the three-dimensional model 302 at each Z coordinate. In additive manufacturing, the position where the modeling material should be discharged is calculated based on the slice data 312, and the trajectory along which the modeling material is discharged becomes the tool path 320.

The control data 204 is a set of control codes that control the 3D modeling device 110 during modeling, such as tool path data and temperature control. An example of the control data 204 is, but is not limited to, G-code.

Refer to FIG. 2 again. The information processing device 150 and the three-dimensional modeling device 110 are connected via a predetermined communication path. The communication path is a communication path that connects nodes and enables communication using a wired LAN (Local Area Network), a wireless LAN, a USB (Universal Serial Bus) cable, or the like. In the embodiment described below, the information processing device 150 and the three-dimensional modeling device 110 exchange data via the communication path, but this is not limited to this. Data may be exchanged between the information processing device 150 and the three-dimensional modeling device 110 using a non-volatile storage medium such as a USB memory or an SD (registered trademark) card without using a communication path.

The 3D modeling device 110 models a 3D object based on a control code included in the control data 204 received from the information processing device 150. The 3D modeling device 110 includes a storage unit 211, a system controller 212, and an engine controller 216.

The system controller 212 receives the control data 204 via the communication path, extracts a control code, and transmits it to the engine controller 216. It also receives sensor data and the like from the engine controller 216 and analyzes the cause of quality defects. The system controller 212 is generally composed of a storage device such as a CPU (Central Processing Unit) and memory.

The accumulation unit 211 is a memory area that stores acquired sensor data, etc., and is composed of storage such as a hard disk drive (HDD) or a solid state drive (SSD).

The engine controller 216 is a controller that extracts and analyzes the control code received from the system controller 212 one command at a time, and controls the 3D modeling device 110. In the embodiment described below, the engine controller 216 simultaneously acquires the time when the control code command was issued and the sensor data at that time, and stores the sensor data in association with the time. The engine controller 216 generally includes a CPU and an I/O (Input/Output) device for outputting control signals.

The three-dimensional modeling apparatus 110 further includes a nozzle temperature sensor 220, a motor current sensor 222, a motor speed detection sensor 224, a filament supply unit 226, a heater drive unit 228, a plate drive unit 230, and a head drive unit 232. These components are connected to the engine controller 216, and operate upon receiving control signals output from the engine controller 216, outputting sensor measurement values to the engine controller 216, or both.

The heater driving unit 228 is composed of a nozzle that ejects the modeling material, a heater for heating the modeling plate, and hardware and software for driving the heater. Note that various heaters are used in various positions in the 3D modeling device 110.

The nozzle temperature sensor 220 is a sensor that detects the temperature of the area heated by the heater. The nozzle temperature sensor 220 is generally composed of a thermocouple or the like. In addition to the nozzle temperature sensor 220, other temperature sensors are provided and used in pairs with the heater.

The head drive unit 232 is a drive means for moving the head 112 on which the nozzle and extruder are mounted in the XY direction. The plate drive unit 230 is a drive means for moving the modeling plate 114 in the Z direction. The head drive unit 232 and the plate drive unit 230 each include a drive motor, a mechanical mechanism for transmitting drive (belt, ball screw, etc.), and a sensor for detecting position information. The motor is not particularly limited, but a servo motor or a stepping motor can be used. The head drive unit 232 and the plate drive unit 230 are configured to work together to drive the nozzle tip, which is the modeling position, in three dimensions using the XYZ drive means to perform modeling.

The filament supply unit 226 is a driving means for sending the amount of filament (modeling material) required for modeling to the nozzle. The filament supply unit 226 is also called an extruder, and is composed of a gear for gripping the filament and a motor for driving the gear.

The motor current sensor 222 is a current sensor that measures the motor drive current to measure the load of each motor. The motor speed detection sensor 224 is a means for detecting the speed of each motor. The motor speed detection sensor 224 detects the speed by measuring the number of rotations of the motor over a certain period of time using an encoder and a timer, etc.

In the embodiment described, the information processing device 150 converts the 3D model data 202 into control data 204 including a control code used by the 3D modeling device 110 by the slicer software 252. The control data 204 is transmitted to the 3D modeling device 110 via a communication path. The 3D modeling device 110 controls heaters and motors based on the control data 204 to model a 3D object.

However, the present invention is not limited to the above embodiment, and the control data 204 may be generated on the 3D modeling device 110 side. Furthermore, instead of the 3D modeling device 110 and the information processing device 150, an external server may be configured to generate the control data 204. In addition, when the control data 204 is generated on an external server, the server may be an on-premise external server, or the control data generation process may be performed on a server that can be connected via the internet, also referred to as the cloud.

In addition, in the embodiment shown in FIG. 2, the web browser 254 on the information processing device 150 can be used to access the system controller 212 of the three-dimensional modeling device 110 and to refer to various settings and quality data described below.

Figure 4 shows the hardware configuration included in the three-dimensional modeling device 110 of the first embodiment. The hardware configuration shown in Figure 4 is, for example, that of the system controller 212 and engine controller 216 described above.

The controllers 212, 216 are primarily comprised of a CPU 12, a ROM 14, a RAM 16, an auxiliary storage device 18, a storage medium reading device 20, an input device 22, a display device 24, and a communication device 26.

The CPU 12 is a circuit that is composed of a microprocessor and its peripheral circuits and controls the entire device. The ROM 14 is a memory that stores a specific control program executed by the CPU 12. The RAM 16 is a memory that the CPU 12 uses as a working area when executing the specific control program stored in the ROM 14 and performing various controls.

The auxiliary storage device 18 is a device that stores various information including a general-purpose OS and various programs, and is a non-volatile storage device such as an HDD, SSD, or SD (registered trademark) card. The accumulation unit 211 shown in FIG. 2 can be replaced by the auxiliary storage device 18. The storage medium reading device 20 is a device that inputs information from an external storage medium such as a CD (Compact Disk), DVD (Digital Versatile Disc), or USB (Universal Serial Bus) memory.

The input device 22 is a device that allows the user to perform various input operations, and includes a mouse, a keyboard, and a touch panel switch that is superimposed on the display screen of the display device 24. The display device 24 is a device that displays various data on the display screen. The display device 24 is composed of, for example, an LCD (Liquid Crystal Display), an organic EL display, or a CRT (Cathode Ray Tube). The communication device 26 is a device that communicates with other devices via a network. It supports communication according to various network forms, including wired networks and wireless networks.

Note that while the hardware configuration of the system controller 212 and the engine controller 216 has been described with reference to FIG. 4, the information processing device 150 can also be realized with a similar hardware configuration, and various processes can be realized depending on the installed software.

The mechanism for controlling the head 112 and modeling plate 114 that constitute the 3D modeling device 110 will be described below with reference to FIG. 5. FIG. 5 is a configuration diagram that explains the configuration around the nozzles provided in the 3D modeling device 110 of the first embodiment. Please note that in FIG. 5, the various sensors 222, 224 shown in FIG. 2 are shown for each representative motor.

The head 112 includes a nozzle 115, a filament supply unit 226, a heat sink 116, and a fan 118. The head 112 is driven in the XY plane by a head drive unit 232.

Nozzle 115 is made by processing metal such as stainless steel or brass, but is not limited to this, and has a tubular shape with a hollow interior. The tip of nozzle 115 has a narrowed inner diameter, and a small hole for ejection (with a diameter of about 0.3 to 0.5 mm, but is not limited to this) is opened. The tip of nozzle 115 (downstream in the feed direction of filament 106) and the rest of the pipe part may be separated, but here, the tip and pipe part are referred to as nozzle 115.

A heating block 120 is disposed near the tip of the nozzle 115 so as to be in close contact with the nozzle 115. A heater 229, which is a heating means, is disposed within the heating block 120, and is configured to transfer heat from the heater 229 to the nozzle 115. A nozzle temperature sensor 220 is also disposed in the heating block 120, and a controller (the engine controller 216 or another temperature control controller) controls the heater 229 to heat the nozzle 115 to a predetermined temperature determined according to the type of filament material and the nozzle shape while reading a signal indicating the temperature from the sensor.

On the other hand, a cooling block 122 is arranged on the end side of the nozzle 115 facing the heating block 120 (referred to as the rear end side; the upstream side in the feed direction of the filament 106) so as to be in close contact with the nozzle 115. As an example, the cooling block 122 is connected to a heat sink 116, and an air-cooling structure is added to the heat sink 116, which cools by blowing air with an electric fan 118.

The filament 106 is inserted into the nozzle 115 from the rear end side by the extruder, and melts at the tip by heating the nozzle 115, and liquid modeling material 104 is extruded. Various types of motors can be used for the extruder, but a servo motor or a stepping motor can be used from the viewpoint of precisely controlling the amount of filament feed.

In the case of a servo motor, the amount of movement and rotation speed are detected by an encoder connected to the motor shaft, and feedback control is used to control the motor rotation speed and, ultimately, the filament feed speed. In addition, the motor load can be quantified by measuring the current value flowing to the motor. In addition, when using a stepping motor, an encoder can be added to obtain a configuration similar to that described above.

The nozzle 115 is heated at the tip and cooled at the rear, so a temperature gradient is generated within the nozzle 115, with the highest temperature near the heating block 120 and the lowest temperature near the cooling block 122. The filament 106 inserted into the nozzle 115 is a resin, and so the melting point is determined for each material. In the temperature range above the melting point, the filament becomes liquid, and below the melting point, it becomes solid, but in reality, it can be in a semi-solid state with a certain temperature range. In order to make the tip of the nozzle 115 liquid (fluid state), the temperature is set higher than the melting point from the periphery of the heating block to the tip of the nozzle 115. From there, the temperature inside the nozzle decreases as it approaches the rear end of the nozzle 115, and the position of the "liquid surface" is determined, which is the boundary where the filament does not melt. At the liquid surface, the material is in a semi-solid state close to solid, and the semi-solid resin is in a state of capping the liquid resin.

During ejection, the semi-solid lid is pushed by sending the filament 106 toward the tip of the nozzle 115, and by applying a force to compress the liquefied material, the liquid resin 104 can be ejected out from the hole at the tip of the nozzle 115. In this way, the model 102 is formed on the modeling plate 114.

Although 3D modeling devices have many advantages, they make it difficult to inspect the inside of the model, and it is difficult to ensure that the internal quality of the resulting 3D model, which cannot be seen from the outside, is being maintained.

In 3D modeling devices, modeling can sometimes fail, but the failure cannot be easily identified and the reason for the failure, such as not reaching the target quality, may become clear after an internal investigation. 3D modeling takes a certain amount of time, so if it is discovered that the quality is poor after a long period of modeling, not only the material but also the time spent on modeling is wasted, which affects costs and productivity. If the cause of errors or quality defects is not adequately analyzed, quality defects can occur frequently.

However, in the case of conventional 3D modeling devices, there are known techniques for detecting quality by using a camera or the like to capture images of the sliced surface or the entire model during modeling, or by acquiring and judging specific sensor values. However, using these techniques alone, it is difficult to analyze and identify the cause of poor quality. Furthermore, it is not possible to fully consider the quality of the 3D model (finished product).

The 3D modeling device 110 according to this embodiment acquires multiple sensor data during 3D modeling as predetermined information for analyzing and identifying the cause of poor modeling quality. The 3D modeling device 110 then outputs quality information of the 3D object obtained by 3D modeling based on the predetermined information. Preferably, the multiple sensor data are recorded with a correspondence between the acquisition timing and local data of the input data used for modeling (each control code and each command or command group therein). This allows the 3D modeling device 110 to evaluate poor quality of the object and output the evaluation results, and when poor quality is detected, to analyze the cause in detail. The 3D modeling device 110 constitutes a data output device in this embodiment that executes a data output method for outputting quality information.

The above-mentioned sensor data can include, for example, measurement information measured by measuring means such as the X current sensor 222x, Y current sensor 222y, X speed sensor 224x, and Y speed sensor 224y of the head drive unit 232 shown in FIG. 4, the Z current sensor 222z and Z speed sensor 224z of the plate drive unit 230, and the extruder current sensor 222e and extruder speed sensor 224e of the filament supply unit 226.

In the embodiment described below, each layer being modeled will be referred to as a "modeling layer", the assembly of multiple layers that have been modeled will be referred to as a "modeled object", and the completed structure after the modeling process is completed will be referred to as a "three-dimensional modeled object".

The functional configuration for performing 3D modeling while acquiring quality data will be described below with reference to FIG. 6. FIG. 6 is a functional block diagram showing a more detailed configuration of the system controller 212 and engine controller 216 that constitute the 3D modeling device 110 according to the first embodiment.

As shown in FIG. 6, the system controller 212, more specifically, includes an analysis unit 213, a quality data recording unit 214, and a quality data output unit 215. The engine controller 216 includes a sensor information acquisition unit 217, an error determination unit 218, and a quality data transmission unit 219.

The engine controller 216 extracts and analyzes the control code received from the system controller 212 one command at a time, and executes the modeling process. In this embodiment, the engine controller 216 determines whether an error has occurred during the modeling process, based on sensor data acquired, preferably in real time, during the modeling process.

More specifically, the sensor information acquisition unit 217 acquires sensor data from various sensors (220, 222, 224) and the like. The sensor data is time-series data covering multiple points in time of measured values by each sensor. In this embodiment, the sensor information acquisition unit 217 constitutes an acquisition means for acquiring the sensor data as predetermined information for three-dimensional modeling.

The error determination unit 218 is a determination means that performs simple error determination based on the sensor data acquired by the sensor information acquisition unit 217. Here, the simple error determination performed by the error determination unit 218 aims to avoid danger to the user and reduce damage to the machine, and it is desirable to perform error determination instantly based on the sensor value. Therefore, rather than performing complex determination by referring to multiple sensor values, the determination is performed using simple determination conditions such as threshold determination in which a threshold value that is regarded as an error is set for a specified sensor value, or an event in which a specified sensor value exceeds the threshold value a specified number of times or more.

The quality data transmission unit 219 transmits quality data to the system controller 212 based on the sensor data acquired by the sensor information acquisition unit 217. Here, quality data is a general term for all data that may relate to the quality of a three-dimensional object. The quality data may include the sensor data acquired by the sensor information acquisition unit 217 when three-dimensional modeling is performed based on each command of the input control code, and the control code used in the modeling process. Each measurement value at one or more points in time in the sensor data, the control code, or one or more commands that constitute the control code are associated with each other by time information such as a timestamp.

The association may be based on the above-mentioned time, or on information indicating a relative time based on a predetermined point in the three-dimensional modeling (e.g., the start time of modeling) or on information indicating the correspondence between the sensor data and the control code. Regarding the information indicating the correspondence, for example, the sensor data measured within a frame section may be recorded in association with the control code executed within the frame section in frame units of a predetermined time interval.

The sensor data includes at least one measurement value selected from the group consisting of the current of one or more motors equipped in the 3D modeling device 110, the speed of one or more motors equipped in the 3D modeling device 110, and the temperature of one or more parts of the 3D modeling device 110.

2 also illustrates the configuration of the 3D modeling apparatus 110 according to another embodiment, which may include an imaging device 234 surrounded by a dashed line, a 3D measurement device 236 surrounded by a dashed line, or both. In this case, the sensor data may further include image information obtained by photographing the object being modeled by the imaging device 234 and 3D measurement information obtained by 3D measuring the object being modeled by the 3D measurement device 236.

In addition to the sensor data and control code, the quality data may also include the results of the simplified error determination described above, setting information for 3D modeling, and device status information during modeling. Here, the setting information for the 3D modeling device may include the time when modeling began, and the speed, temperature, and rotation speed of various means that are set as initial values. Furthermore, in the event of an error, the setting information that has been changed as a result of the error may be included in the setting information for the 3D modeling device.

The system controller 212 extracts a control code from the control data 204 and transmits it to the engine controller 216. It also receives quality data from the engine controller 216, accumulates the quality data for later analysis, and analyzes the cause of quality defects. The system controller 212 acquires and analyzes sensor data at longer intervals than the engine controller 216, and generates quality information for the object being modeled and the completed structure after the modeling process is completed, that is, the three-dimensional object.

The analysis unit 213 of the system controller 212 analyzes the received quality data and judges whether the quality of the object being modeled and the three-dimensional object is acceptable or unacceptable. The quality information, which is the result of the judgment as to whether the quality of the three-dimensional object is acceptable or unacceptable, and the judgment result as to whether the quality of the object is acceptable or unacceptable at each point during modeling, are included in the accumulated quality data. Here, the pass/fail quality of the three-dimensional object may include an evaluation of the quality of the entire three-dimensional object, one or more parts that make up the three-dimensional object, or a combination of these. The analysis unit 213 constitutes the analysis means in this embodiment.

As described above, while the engine controller 216 is required to make an error judgment immediately, the system controller 212 receives quality data at an appropriate timing and analyzes whether or not there is a quality defect. The quality defect is preferably a phenomenon that is not detected as a mechanical error but has an effect on the molding quality.

Although the analysis method is not particularly limited, in the embodiment described below, the analysis by the analysis unit 213 is characterized by being based on longer-term information and including more complex analysis processing compared to the simplified error judgment by the error judgment unit 218 of the engine controller 216. For example, when the error judgment is a single threshold condition or a threshold condition for the number of events that satisfy the threshold condition, a method of judging based on a logical sum or logical product condition that combines multiple threshold conditions for the sensor value or threshold conditions for the number of times can be mentioned. Alternatively, a method of applying machine learning or artificial intelligence technology to make a model learn patterns observed in the sensor data in advance when quality is poor, and making a judgment using the learned model can be mentioned. Note that the input to the condition or learning model is not limited to sensor data, and the target control code can be added to the input, and may include the judgment result of the engine controller 216, setting information and device status information for the three-dimensional modeling, image information, and three-dimensional measurement information.

The quality data recording unit 214 receives the quality data transmitted by the engine controller 216 from the quality data transmission unit 219 and records it in the storage unit 211. The quality data recording unit 214 also records the analysis results by the analysis unit 213 in the quality data in the storage unit 211.

The quality data output unit 215 can output at least the quality information of the three-dimensional object, for example, to the display device 24 for display, output to an external device via the communication device 26, or output from a connected image forming device (printer or multifunction device). The quality data output unit 215 can also output all or part of the quality data, including sensor data and control codes, together with the quality information of the three-dimensional object. The quality data output unit 215 constitutes the output means in this embodiment.

The modeling process executed by the three-dimensional modeling system 100 of the first embodiment will be described below with reference to Figs. 7 to 10. Fig. 7 is a flowchart showing the overall flow of the modeling process executed by the three-dimensional modeling system 100 of the first embodiment. Fig. 8 is a flowchart showing the process of modeling while acquiring quality data, executed by the three-dimensional modeling device 110 of the first embodiment.

The modeling process shown in FIG. 7 starts at step S100 in response to an instruction from a user. Note that in the flowchart shown in FIG. 7, the process performed by the information processing device 150 is on the left side, and the process performed by the 3D modeling device 110 is on the right side.

In step S101, the information processing device 150 causes the slicer software 252 to read the specified three-dimensional model data 202. The designation of the three-dimensional model data 202 is included, for example, in the instruction from the user in step S100. In step S102, the information processing device 150 slices the three-dimensional model defined by the read three-dimensional model data 202 using the slicer software 252, and generates control data 204 including a tool path. In step S103, the information processing device 150 transfers the control data 204 to the three-dimensional modeling device 110.

In step S104, the 3D modeling device 110 receives control data transmitted from the information processing device 150. In step S105, the 3D modeling device 110 waits for an instruction to start modeling processing from the user via, for example, a touch panel provided on the 3D modeling device 110, and loops through step S105 until the instruction is received. If it is determined in step S105 that an instruction to start modeling has been received from the user (YES), the process proceeds to step S106. In step S106, the 3D modeling device 110 performs 3D modeling while acquiring quality data, and ends this process in step S107.

The process shown in FIG. 8 is called by the process of step S106 in the overall flow shown in FIG. 7, and starts from step S200. Note that in the flowchart shown in FIG. 8, the processes handled by the system controller 212 in the 3D modeling device 110 are on the left side, and the processes handled by the engine controller 216 are on the right side.

In step S201, the system controller 212 instructs the engine controller 216 to start modeling and transmits a control code. In step S202, the engine controller 216 starts modeling. In step S203, the engine controller 216 extracts the next code to be executed from the control code.

Figure 9 illustrates an example of the data structure of the control code processed by the three-dimensional modeling apparatus 110 of the first embodiment. The control code 330 illustrated in Figure 9 illustrates a case where the control code 330 is a G-code, with each line forming one command (instruction), and the control code 330 may include multiple lines. In Figure 9, "G1" is a command that specifies the linear movement of the nozzle (head) from its current position to a coordinate position represented by the (X, Y, Z, E) coordinate system. Note that unit is mm. Note that E represents the one-dimensional coordinate of the filament. F represents the nozzle (head) movement speed, and is expressed in mm/min.

Referring again to FIG. 8, in step S204, the engine controller 216 records the code to be executed together with the time as quality data, and executes the code. In step S205, the engine controller 216 acquires sensor data while the code is being executed, and records the acquired sensor data together with the time as quality data.

In step S206, the engine controller 216 performs a simple error determination. If it is determined in step S206 that there is no error (no error), the process proceeds to step S207. In step S207, the engine controller 216 determines whether or not the execution of the current code has been completed. If it is determined in step S207 that the execution of the code has not yet been completed (NO), the process returns to step S205, and the acquisition of sensor data continues. On the other hand, if it is determined in step S207 that the execution of the code has been completed (YES), the process proceeds to step S208. Also, if it is determined in step S206 that there is an error (error present), the process branches to step S208.

In step S208, the engine controller 216 transmits the recorded quality data to the system controller 212. This quality data may include the executed control code, sensor data, simple error determination results, and time information linking these pieces of information, as described above.

In step S209, the system controller 212 accumulates the quality data received from the engine controller 216 in the accumulation unit 211. In step S210, the system controller 212 performs an analysis based on the received quality data using the analysis unit 213. In step S211, the system controller 212 determines whether or not there is a quality defect as a result of the analysis in step S210. If it is determined in step S211 that there is a quality defect (YES), the process branches to step S212. In step S212, the system controller 212 notifies the engine controller 216 of the quality defect and proceeds to step S213. On the other hand, if it is determined in step S211 that there is no quality defect (NO), a notification of good quality is appropriately given, and the process proceeds directly to step S213.

In step S213, the engine controller 216 determines whether or not to end the modeling. If it is determined in step S213 that the modeling is not to be ended (NO), the process loops to step S203 and proceeds to processing of the next code. On the other hand, if it is determined in step S213 that the modeling is to be ended (YES), the process branches to step S214.

Here, if the code that has completed execution is the final code and no quality defect has been notified, the modeling is deemed to have been completed successfully, and the modeling ends. Also, during operation, the engine controller 216 determines whether an error has occurred based on the acquired sensor values. If an error occurs, quality data is sent to the system controller 212 and accumulated, and then the modeling is determined to have ended in the modeling end determination in step S213, and modeling ends. Also, if a quality defect is found as a result of the analysis in step S210, the modeling is determined to have ended in the modeling end determination in step S213, and modeling ends.

However, since the three-dimensional printing device 110 often prints multiple models at a time, it is preferable that even if one object is determined to be of poor quality, the printing process can continue for the other objects. When printing multiple objects in parallel, it is preferable to stop subsequent printing processes for a specific object with poor quality, while continuing printing processes for other objects with good quality. Also, since there are degrees of quality, in the case of a slight deterioration in quality, it is possible to record this fact while continuing printing processes.

In step S214, the engine controller 216 notifies the system controller 212 of the end of modeling. In step S215, the system controller 212 performs modeling completion processing and outputs quality information, and in step S216, the processing ends and control is returned to the processing shown in FIG. 7.

As described above, if the three-dimensional object is modeled to the end without any quality defects, quality information indicating that the quality has passed is output. If a partial quality deterioration of the three-dimensional object as described above is recorded, information indicating the quality deterioration may be included in the quality information. Furthermore, if an error or quality defect occurs and the modeling of the three-dimensional object is stopped before it is completed, failing quality information is output. Furthermore, in addition to failing quality information, accumulated quality data (e.g. data around the time when the quality defect occurred) can also be output in order to identify the cause by performing a more advanced analysis than manual analysis.

The quality information may be displayed on a display device such as a touch panel provided on the 3D modeling device 110 or a display of the information processing device 150 connected to the 3D modeling device 110, or may be printed as a paper quality guarantee certificate. Alternatively, an identification medium such as an ID tag or a QR (registered trademark) code sheet may be attached to the 3D object, and the quality information may be stored in the identification medium. The quality information may also be output simultaneously with the notification of the completion of modeling, or may be output before or after the notification of the completion of modeling.

Figure 10 illustrates an example of the data structure of quality data 340 recorded by the three-dimensional modeling device 110 of the first embodiment. The quality data 340 shown in Figure 10 is a chronological arrangement of data acquired as the modeling process progresses. The quality data 340 includes a number field 341, a time field 342, a type field 343, a value field 344, and a unit field 345.

In the time field 342, time information is entered in the format of hours:minutes:seconds:milliseconds. However, the time may be a timer value with the start of modeling as the reference (0), or normal time may be used. In the type field 343, a type is entered that identifies whether the record represents a command or a sensor measurement value. In the value field 344, the content of the command or the sensor measurement value is entered. In the unit field 345, information on the unit of the numerical value entered in the value field 344 is entered as necessary.

When a molding defect occurs, analyzing the cause leads to improved productivity in subsequent molding processes. The system controller 212 stores sensor data and control codes for each molding as quality data so that they can be referenced in chronological order. By identifying the location where the error or quality defect occurred and referencing the control code at the time the error or quality defect occurred, or for a certain period of time before the error or quality defect occurred, it becomes possible to retroactively analyze what molding pattern was formed when the quality defect occurred and what the state of the motor and heater was at that time. Machine learning and artificial intelligence can also be used for the analysis.

In addition, if the analysis unit 213 detects a quality defect during modeling, it is possible to stop further modeling processing of the object with the defective quality, thereby preventing the completion of a three-dimensional object with poor quality, which would result in the waste of materials and time spent on modeling, and is advantageous in terms of cost and productivity.

The quality data is stored in the storage unit 211 by the system controller 212, but if the volume becomes large, the quality data may be compressed and stored, or data with no quality problems may be thinned out and stored. It is also preferable to configure the system controller 212 to have functions such as a web server or file server so that the stored quality data can be obtained via a network. For example, the web browser 254 shown in FIG. 2 can be used to access the web server of the system controller 212 of the 3D modeling device 110 and obtain the quality data.

Figure 11 illustrates an example of the data structure of quality data 350 recorded by the three-dimensional modeling apparatus 110 of another embodiment. The quality data 350 shown in Figure 11 is obtained by adding log information 356a to 356d, which is device status information during modeling, to the quality data 340 shown in Figure 10. By adding the log information 356a to 356d, it becomes possible to analyze the cause of software-induced errors and errors and quality defects that cannot be detected by sensor data alone. By associating the sensor data with the operation of the software, analysis becomes even easier. In addition, it becomes possible to grasp the status of the engine and engine controller 216 in text, which improves the readability of the data and is expected to improve the user interface. In addition, it becomes possible to grasp the sensor information immediately before the error, which makes it easier to analyze the cause of the error. Note that the log information is output due to the status judgment, including the above-mentioned error judgment, of the engine controller 216, and may also include events such as "build Start".

Figure 12 illustrates an example of the data structure of quality data 360 recorded by a three-dimensional modeling apparatus in yet another embodiment. The quality data 360 shown in Figure 12 is an example in which setting value information 366a, 366b is added to the quality data 350 shown in Figure 10. This setting value information 366a, 366b can be used to analyze the cause of poor quality. Furthermore, if an error occurs, setting information that has been changed as a result of the error may be recorded. By including setting values in the analysis, it is possible to further improve the accuracy of the analysis.

The 3D modeling system 100 according to the second embodiment will be described below with reference to Figs. 2, 7, and 13 to 16. The second embodiment includes an imaging device 234 shown by the dashed line in Fig. 2. Note that, for matters not specifically described in the second embodiment, the same configuration as in the first embodiment is adopted.

Figure 13 explains the configuration around the nozzle of the three-dimensional modeling apparatus according to the second embodiment. As shown in Figure 13, the imaging device 234 is provided in the head 112 and is configured to capture an image of the modeling layer from above at any timing during the modeling process and obtain image data (image information) of the modeling surface.

Figure 14 is a flowchart showing the process of modeling while acquiring quality data, which is executed by the three-dimensional modeling device of the second embodiment. Note that the second embodiment also performs the same overall process as that shown in Figure 7.

The process shown in FIG. 14 is called by the process of step S106 in the overall flow shown in FIG. 7, and starts from step S300. Note that in the flowchart shown in FIG. 14, as in FIG. 8, the processes handled by the system controller 212 are on the left side, and the processes handled by the engine controller 216 are on the right side.

The processing in steps S301 to S307 is the same as the processing in steps S201 to S207 shown in FIG. 8, except for the branching destinations in steps S306 and S307, so a detailed explanation will be omitted below.

If it is determined in step S307 that the execution of the code has been completed (YES), the process proceeds to step S308. In step S308, the engine controller 216 determines whether the modeling process for one layer has been completed. If it is determined in step S308 that the modeling process for one layer has been completed (YES), the process proceeds to step S309.

In step S309, the engine controller 216 captures an image using the imaging device 234, and acquires image information of the printing surface as quality data (sensor data). In step S310, the engine controller 216 transmits the recorded quality data to the system controller 212. This quality data may include image information of the printing surface in addition to the control code, sensor data, and simple error determination result executed as described above. Also, if it is determined in step S306 that an error has occurred (Error Present), and if it is determined in step S308 that printing of one layer has not yet been completed (NO), the process branches to step S310.

In step S311, the system controller 212 accumulates the quality data received from the engine controller 216 in the accumulation unit 211. In step S312, the system controller 212 performs an analysis based on the received quality data using the analysis unit 213. The analysis in step S312 may include an analysis of the image information of the printing surface.

Steps S313 to S318 are similar to the processing of steps S211 to S216 shown in Figure 8, so a detailed explanation will be omitted.

The difference between the flow of the embodiment shown in FIG. 8 and the flow of the embodiment shown in FIG. 14 is mainly that image data of the modeling layer (image information of the modeling surface) is acquired by the imaging device 234 each time one layer is modeled, and the system controller 212 performs an analysis of quality defects based on the image information of the modeling surface. Note that, although quality defects are determined based on the image information of the modeling surface, the analysis may be performed in combination with an analysis based on sensor data, as in the embodiment shown in FIG. 8.

Figure 15 illustrates an example of the data structure of quality data 370 recorded by the three-dimensional modeling apparatus of the second embodiment. In the second embodiment, image information is stored in the storage unit 211 as a separate file, and the quality data 370 records a record 376 of the time the image data was acquired and the identifier of the image data at that time. In this case, a type indicating that it is an image is entered in the type field 373, and an identifier is entered in the value field 374.

Figure 16 explains the analysis process based on image information performed in the three-dimensional modeling apparatus of the second embodiment. In the analysis, first, three-dimensional drawing is used based on the slice data 380 and tool path data 382 described above, and image data 384 of the modeling surface when ideal output is good quality is generated. Then, in the analysis, the actually acquired image information 386 of the modeling surface is compared with the generated image data 384 of the modeling surface when good quality is generated, and the quality of the modeling layer being modeled is determined. In the actually acquired image information 386 of the modeling surface shown in Figure 16, there is a defect 388, and in this case, it is determined that the quality is poor.

Such analysis can be suitably carried out by applying artificial intelligence such as machine learning or neural networks. However, since the processing load of judging the image is large, it is also contemplated to carry out the analysis of quality defects by performing an analysis such as the logical sum of threshold conditions for multiple sensor values, as in the embodiment shown in FIG. 8, and to accumulate image information as evidence for manual judgment.

By using image information as the subject of analysis, it is possible to improve the accuracy of analyzing the causes of quality defects in three-dimensional objects.

In the second embodiment described with reference to Figures 2, 7, and 13 to 16, image information is acquired as quality data (sensor data) using the imaging device 234. However, a three-dimensional measuring device 236 shown by a dashed line in Figure 2 can be provided together with the imaging device 234 or instead of the imaging device 234. In that case, the quality data (sensor data) includes three-dimensional measurement information obtained by three-dimensionally measuring the object being modeled, and quality defects can be analyzed based on the three-dimensional measurement information.

The three-dimensional measuring device 236 is a device that obtains depth information from a sensor using laser light, stereo vision using compound eyes, or the like. A three-dimensional image can be generated by combining the depth information and image information, but for simplicity, it is sufficient to obtain depth information corresponding to two-dimensional coordinates. Some three-dimensional measuring devices 236 include an imaging element, so the imaging device 234 can be omitted. The three-dimensional measuring device 236 is also provided in the head 112, similar to the imaging device 234 shown in FIG. 13.

In the second embodiment, two-dimensional image information 384 of the printing surface in the case of good quality was generated based on the slice data 380 and tool path data 382 described above, but when the three-dimensional measuring device 236 is used, a three-dimensional image is generated. And since the image information 382 of the actually acquired printing surface is also acquired as a three-dimensional image measured in three dimensions, the two can be compared. Preferably, to simplify the process, the XY coordinate positions of the three-dimensional image in the case of good quality and the three-dimensional image measured in three dimensions are aligned, and a judgment can be made by comparing only the Z value.

By using 3D measurement information as the subject of analysis, it is possible to improve the accuracy of analyzing the causes of quality defects in 3D objects.

The following describes a three-dimensional modeling system 100 according to the third embodiment with reference to Figs. 17 and 18. The third embodiment includes a server device 170 in addition to the information processing device 150 and three-dimensional modeling device 110 shown in Fig. 2. Note that, for matters not specifically described in the third embodiment, the same configuration as in the first or second embodiment is adopted.

Fig. 17 shows the system configuration of a 3D modeling system in the third embodiment. The server device 170 shown in Fig. 17 is a cloud server or an on-premise server via the internet, and is connected to the 3D modeling device 110 via a communication path such as a network. The hardware configuration of the server device 170 can be the same as that described with reference to Fig. 4.

Note that in FIG. 17, the server device 170 is depicted as being connected to only a single 3D modeling device, but the server device 170 is preferably connected to multiple 3D modeling devices 110, and collects quality data acquired during modeling processing performed by the multiple 3D modeling devices 110, and stores the data in the storage unit 272.

In the embodiment described, analysis of quality defects based on the above-mentioned quality data is performed by both the system controller 212 and the server device 170. The system controller 212 requires a certain degree of immediacy in analysis, although not to the same extent as the engine controller 216. On the other hand, the server device 170 requires accuracy of analysis rather than immediacy.

Fig. 18 is a flowchart showing part of the process of modeling while acquiring quality data, which is executed by the three-dimensional modeling apparatus of the third embodiment. Note that the flowchart shown in Fig. 18 shows the part that corresponds to steps S311 to S314 surrounded by dashed lines in the flowchart shown in Fig. 14, and the following explanation will be given with reference to Fig. 14 as well.

When the engine controller 216 transmits the quality data in step S310, the system controller 212 accumulates the quality data received from the engine controller 216 in the accumulation unit 211 in step S311. In step S312, the system controller 212 performs an analysis based on the received quality data using the analysis unit 213.

Meanwhile, after receiving the quality data, in parallel with the analysis in step S312, in step S400, the system controller 212 transmits the received quality data to the server device 170.

In step S401, the server device 170 accumulates the quality data received from the system controller 212 in the accumulation unit 272. In step S402, the server device 170 performs analysis based on the received quality data. The analysis method in step S402 is not particularly limited, but may be based on longer-term information and include more complex analysis processing (requiring more computational resources) compared to the analysis by the analysis unit 213.

In step S403, the server device 170 determines whether or not there is a quality defect based on the results of the analysis in step S402. If it is determined in step S403 that there is a quality defect (YES), the process branches to step S404. In step S404, the server device 170 notifies the system controller 212 of the 3D modeling device 110 of the quality defect. On the other hand, if it is determined in step S403 that there is no quality defect (NO), the server device 170 appropriately notifies the system controller 212 that there is no quality defect.

In step S405, the system controller 212 receives the quality judgment result from the server device 170. In step S313, the system controller 212 judges whether or not there is a quality defect based on the results of the analysis in steps S312 and S402. If it is judged in step S313 that there is a quality defect (YES), the process branches to step S314.

In step S314, the system controller 212 notifies the engine controller 216 of the quality defect, and the process proceeds to step S315 shown in FIG. 14. On the other hand, if it is determined in step S313 that there is no quality defect (NO), the process proceeds directly to step S315 shown in FIG. 14. The subsequent processes are the same as those in steps S213 to S216 shown in FIG. 8 and steps S315 to S318 shown in FIG. 14, and therefore will not be repeated.

In the flowchart shown in FIG. 18, the analysis is performed by the server device 170, and the quality judgment results are fed back to the 3D modeling device 110. However, in other embodiments, the feedback may be omitted, and the server device 170 may simply store the results in the storage unit 272.

The server device 170 is used to perform more accurate quality assessments and to take into account deterioration over time of the 3D modeling device 110. In addition, the server device 170 is likely to have fewer constraints on computational resources, such as storage capacity and computing power, than the 3D modeling device 110 and the information processing device 150, and may be able to utilize more resources. Therefore, by utilizing the abundant computational resources of the server device 170, detailed analysis that is not possible on the 3D modeling device 110 side becomes possible.

The server device 170 is also in an environment where it can collect a large amount of information from multiple 3D modeling devices 110. This is particularly suitable for mechanisms that require learning, such as machine learning and artificial intelligence. Furthermore, by accumulating changes over time in the same 3D modeling device 110 and comparing it with past information, it is possible to diagnose faults in the 3D modeling device 110 and detect signs of faults in advance. This allows preventive measures to be taken in advance, reducing downtime for the 3D modeling device 110.

In the above-described embodiments, the quality data can include setting information for 3D modeling and device status information during modeling. On the other hand, acquisition of this setting value information and device status information is premised on the ability to acquire logs of device status information and setting value information by some means. However, peripheral devices connected to the 3D modeling device 110 often use devices manufactured by a manufacturer different from that of the 3D modeling device 110 for each process, and it can be difficult to incorporate the information required for analysis into logs, etc.

The following describes a fourth embodiment that makes it possible to obtain device status information and setting value information of peripheral devices as quality data, even when it is difficult to obtain the information required for analysis by incorporating it into a log or the like.

Fig. 19 is a diagram showing a schematic configuration of the entire 3D modeling system 400 in the fourth embodiment. As shown in Fig. 19, the 3D modeling system 400 includes a 3D modeling device 110 that models a 3D object, one or more peripheral devices 410A, 410B, one or more monitoring devices 420A, 420B provided for each peripheral device 410, and a management device 450.

The 3D modeling device 110 receives data for forming a desired 3D object, and forms the 3D object based on the data. The peripheral devices 410 are devices connected downstream of the 3D modeling device 110, and are devices that further process the products generated by the 3D modeling device 110. The 3D modeling device 110 and the peripheral devices 410 are connected via an appropriate transport path, and the products of the 3D modeling device 110 are delivered to each peripheral device 410 via the transport path.

Examples of peripheral equipment 410 include, but are not limited to, a solvent drying device, an excess powder removal device, a degreasing and sintering device, and the like, and may be any device that performs any processing used during 3D modeling or in post-processing of the 3D modeling process. Peripheral equipment 410 may be manufactured by a manufacturer separate from 3D modeling device 110 for each process, but is not limited to this.

The management device 450 is connected to the 3D modeling device 110 and the monitoring device 420 via a wired or wireless connection or a network. The monitoring devices 420A and 420B are provided close to the corresponding peripheral devices 410, and acquire images of the display units of the corresponding peripheral devices 410 and transmit the information contained therein to the management device 450. The management device 450 acquires and manages the information acquired from the corresponding peripheral devices 410 from the monitoring device 420.

The management device 450 receives quality data output from the 3D modeling device 110. When the quality information included in the quality data indicates poor quality, the management device 450 requests the monitoring devices 420A and 420B of the peripheral devices 410A and 410B connected to the 3D modeling device 110 to obtain setting information and device status information (1). The monitoring device 420 obtains images of the locations of the connected peripheral devices 410 that indicate setting information, such as the display and dial (2), and notifies the management device 450 of the obtained images (3). The management device 450 associates the obtained information with the input data obtained from the 3D modeling device 110, and stores and manages them.

Figure 20 is a diagram showing the system configuration of a 3D modeling system 400 in the fourth embodiment. The 3D modeling system 400 shown in Figure 20 has parts in common with the system configuration shown in Figure 2, and the following description will focus on the differences.

As shown in FIG. 20, the 3D modeling system 400 includes a 3D modeling device 110, an information processing device 150, a peripheral device 410, a monitoring device 420, and a management device 450. As in the first embodiment, slicer software 252 runs on the information processing device 150. The 3D modeling device 110 includes a storage unit 211, a system controller 212, an engine controller 216, and various sensors 220 to 236. As in the first embodiment, the system controller 212 receives sensor data and the like from the engine controller 216, analyzes the cause of quality defects, and outputs the results to the management device 450.

The peripheral device 410 is a device that further processes the product generated by the three-dimensional modeling device 110. More specifically, the peripheral device 410 includes an input unit 412, a control unit 414, and a display unit 416.

The input unit 412 receives input of information for controlling the peripheral device 410. Examples of information to be input include sensor information, operation unit input information, images, motion detection, etc. In addition to user input, information detected by a sensor may also be input.

The control unit 414 controls the operation of the peripherals based on the information input by the input unit 412. Various functions of the peripheral device 410 are realized by the control by the control unit 414. If the peripheral device 410 is a degreasing/sintering machine, it may include a degreasing section, a sintering section, etc. The control unit 414 also notifies the display unit 416 of the device status and set information.

The display unit 416 displays the device status and information of the peripheral device, and the values input by the input unit 412. In the embodiment described, the display unit 416 is described as displaying and outputting the status of the peripheral device 410 and the input setting information on a display, but in addition to the display, it may also include physical switches, dials, meters, and other items that allow the setting contents and status to be visually determined. The physical switches and dials not only display the currently set values, but are also used when the user enters values, so they may also constitute the input unit 412.

The monitoring device 420 monitors the device operation of the peripheral device 410 and acquires setting information and device status information. The monitoring device 420 may be provided outside the peripheral device 410 or may be built into the peripheral device 410. More specifically, the monitoring device 420 includes a monitoring unit 422 and an acquisition unit 424.

The monitoring unit 422 monitors the peripheral devices 410 connected to the 3D modeling device 110, and further cooperates with the monitoring device 420 corresponding to the 3D modeling device 110 or other peripheral devices 410. The monitoring unit 422 monitors the connected peripheral devices 410 upon receiving instructions from the 3D modeling device 110 or the management device 450.

The acquisition unit 424 acquires information displayed on the display unit 416 of the peripheral device 410 as an image. The method of monitoring and acquiring information is not particularly limited, but may include, for example, capturing images of the control status and screen of a moving part using a camera, a physical switch, and communication with a sensor or device. The acquisition unit 424 can also extract setting information and device status information from the acquired image, and can function as an extraction unit. Expressions such as setting information and device status information are used, but they may be only setting information, only device status information, or both, and refer to at least one of setting information and device status information. By performing the extraction process in each monitoring device 420 instead of the management device 450, it is possible to distribute the load of data storage and processing.

In the embodiment described, the monitoring unit 422 and acquisition unit 424 of the monitoring device 420 constitute a monitoring unit that monitors the peripheral device 410 and acquires the information displayed on the display unit 416 of the peripheral device 410 as an image.

The management device 450 is connected to the monitoring device 420 of the 3D modeling device 110 and the peripheral device 410, and cooperates with them. More specifically, the management device 450 includes a management unit 452, an acquisition unit 454, a storage unit 466, and a comparison unit 458.

The management unit 452 is connected to the monitoring device 420 and the 3D modeling device 110, and can receive information from the 3D modeling device 110 to operate the monitoring device 420 of the peripheral device 410 and manage them. The management unit 452 can also add setting information, device status information, and/or images extracted from images acquired by the acquisition unit 454, link them to the input data, record them, and manage them.

The management unit 452 can acquire information from multiple monitoring devices 420. The management unit 452 can further manage the number of pieces of setting information and device status information that can be retained. The management unit 452 can also manage a quality abnormality possibility flag in association with the input data according to the results of comparison by the comparison unit 458 described below.

The acquisition unit 454 can acquire images acquired by the acquisition unit 424 of the monitoring device 420, setting information, and device status information. If the information is acquired as an image, the setting information and device status information can be extracted from the image, and the acquisition unit 454 can function as an extraction unit. The acquisition unit 454 constitutes an acquisition unit that acquires information displayed on the display unit 416 of the peripheral device 410 from the monitoring device 420.

The storage unit 466 is a non-volatile memory, and holds information on the allowable range of values for each item of the setting information and device status information. The comparison unit 458 compares the values of the items of the setting information and device status information acquired by the acquisition unit 454 with the corresponding allowable ranges stored in the storage unit 466, and notifies the management unit 452 of the comparison result. The comparison unit 458 can also compare the allowable ranges with the values of the corresponding items of the setting information or device status information when information on the allowable ranges of the items of the setting information or device status information is newly stored in the storage unit.

Figure 21 is a flowchart showing the process of acquiring information on the display screen of the peripheral device 410 as quality data in the 3D modeling system 400 in the fourth embodiment. The process shown in Figure 21 starts from step S500, and in step S501, modeling ends with the presence of quality defects.

In step S502, the management device 450 determines whether the modeling being performed uses the connected peripheral device 410, and branches the process depending on the determination result. If it is determined in step S502 that the modeling does not use the peripheral device 410 (NO), the process branches to step S511 and ends this process. On the other hand, if it is determined that the modeling being performed uses the peripheral device 410 (YES), the process proceeds to step S503.

In step S503, the management device 450 requests the monitoring device 420 to acquire the display image of the display unit 416 of the peripheral device 410. In step S504, the management device 450 determines whether or not there is another peripheral device 410 connected to the rear. If it is determined in step S504 that there is a subsequent one (YES), the process returns to step S503, and the process is repeated until the display screen of the display unit 416 of the final peripheral device 410 can be acquired. On the other hand, if it is determined in step S504 that there is no more subsequent peripheral device 410 connected (NO), the process proceeds to step S505. In step S505, the management device 450 links the display image of the display unit 416 of the peripheral device 410 acquired so far to the quality data. By linking and managing the quality data (and thus the input data), it is expected that the analysis speed at the time of quality defects will be improved. In step S506, setting information and device status information are extracted from the acquired display image of the display unit 416.

Figure 22 is a diagram for explaining the process of extracting setting information from the display image of the display unit 416 in the three-dimensional modeling system according to the fourth embodiment. As shown in Figure 22 (A), an image 500 displayed on the display unit 416 of the peripheral device 410 is acquired. As described above, the display unit 416 may include a liquid crystal display, a physical switch, a dial, a meter, etc. In this case, a display image is acquired as an image captured by a camera with such a display unit 416 included in its field of view. Image processing is performed from the image 500 shown in Figure 22 (A), and setting items and setting values 512, etc., included in the processed image 510 shown in Figure 22 (B) can be read.

The setting information may be a value that can be set by the peripheral device, such as temperature or time, and the device status information may be a numerical value that indicates the status of the peripheral device, such as the current temperature or operating value. In the above-described embodiment, a method for extracting information from an image is not specifically mentioned, but known technology can be used and may be implemented by either the monitoring device 520 or the management device 450. In this way, by acquiring the display screen of the peripheral device, even if it is difficult to acquire it as a log, it is possible to acquire information from the displayed image and obtain the necessary information, which makes it possible to assist in identifying the cause when analyzing quality defects. In this way, by converting it into numerical values instead of images, it is possible to reduce the effort required when converting it into analysis software such as a tool.

In step S507, the management device 450 determines whether or not it holds information on the acceptable range of values. Here, it is assumed that the management device 450 and the monitoring device 420 hold information on the acceptable range of values for each item of the setting information and device status information in advance. If it is determined in step S507 that information on the acceptable range of values is not held (NO), the process ends in step S511. On the other hand, if it is determined in step 507 that information on the acceptable range of values is held (YES), the process branches to step S508.

In step S508, the management device 450 compares the extracted setting information and device status information with the range of values stored. In step S509, the management device 450 determines whether the value is outside the range as a result of the comparison. If it is determined in step S509 that the value is within the range (NO), the process ends in step S511. On the other hand, if it is determined in step 509 that the value is outside the range (YES), the process branches to step S510.

In step S510, the management device 450 links the quality data with a quality abnormality possibility flag indicating the possibility of a quality abnormality, and ends this process in step S511. Here, an acceptable range can be stored for each acquired setting information and device status information, and if it is outside this range, it is determined that there is a possibility that the cause of the quality abnormality is, and a quality abnormality possibility flag is further linked to the quality data. This makes it easier to identify causes such as user operation errors or setting errors.

A specific comparison process of numerical ranges will be described below with reference to Fig. 23. Fig. 23 is a diagram for explaining a process of comparing extracted setting information and apparatus status information with a numerical range in a three-dimensional modeling system according to the fourth embodiment. As shown in Fig. 23, the management device 450 or the monitoring device 420 can hold maximum values, minimum values, and allowable values according to the items of setting information and apparatus status information that can be acquired. Then, when the following conditions are met for each of the held values, a quality abnormality possibility flag can be set in association with the quality data.
(1) Maximum value: If the acquired setting value is greater than the maximum value
Maximum value < acquired setting information/device status information value (2) Minimum value: When the acquired setting value is smaller than the value set in the minimum value
Minimum value > Value of acquired setting information/device status information (3) Tolerance value: When the value set in the tolerance value differs from the acquired setting value
Permissible value ≠ Value of acquired setting information/device status information

Please note that the example shown in FIG. 23 is merely an example, and the specific setting values and status information will vary depending on the setting and status items. In addition, when the comparison is performed by the management device 450, the allowable range information of the above-mentioned values can be stored for each pair of the peripheral device 410 and the monitoring device 420.

Figure 24 is a flowchart showing the process of comparing setting information and device status information with range information in a 3D modeling system in the fourth embodiment. The process shown in the flowchart in Figure 21 is a process when numerical range information is already stored when setting information or device status information is acquired. If the setting value range is not stored when setting information or device status information is acquired, the process described in the flowchart in Figure 24 makes it possible to perform a comparison at the point when the range information is stored.

The process shown in FIG. 24 starts at step S600, and in step S601, the management device 450 sets the allowable range information for the values of the setting information and device status information. In step S602, the management device 450 determines whether the corresponding setting information or device status information is held. If it is determined in step S602 that the corresponding information is not held (NO), the process ends in step S606. On the other hand, if it is determined in step S602 that the corresponding setting information or device status information is held (YES), the process branches to step S603.

In step S603, the management device 450 compares the value of the corresponding setting information or device status information item with the tolerance range stored. In step S604, the management device 450 determines whether the value is outside the range as a result of the comparison. If it is determined in step S604 that the value is within the range (NO), the process ends in step S606. On the other hand, if it is determined in step S604 that the numerical value is outside the range (YES), the process branches to step S605. In step S605, the management device 450 associates a quality anomaly possibility flag, which indicates that the quality data is a candidate for an anomaly, with the quality data, and ends the process in step S606.

In this way, when the storage unit 456 stores new acceptable ranges for at least one of the items of the corresponding setting information and device status information, the comparison unit 458 can compare the acceptable ranges with the values of at least one of the items of the corresponding setting information or device status information, and include a quality abnormality possibility flag in the quality data if necessary. By being able to apply the comparison of acceptable ranges to setting information and device status information that are already stored, it becomes possible to easily investigate errors in setting acceptable ranges and patterns of setting values.

Below, with reference to FIG. 25, another process for acquiring information on the display screen of a peripheral device as quality data will be described. FIG. 25 is a flowchart showing another process for acquiring information on the display screen of a peripheral device as quality data in a three-dimensional modeling system in the fourth embodiment.

The process shown in FIG. 25 starts from step S700, and in step S701, the modeling ends with a quality defect. In step S702, the management device 450 determines whether the modeling being performed is a modeling that uses the connected peripheral device 410, and branches the process depending on the determination result. If it is determined in step S702 that the modeling is a modeling that does not use the peripheral device 410 (NO), the process branches to step S711 and ends this process. On the other hand, if it is determined that the modeling being performed uses the peripheral device 410 (YES), the process proceeds to step S703.

In step S703, the management device 450 requests the monitoring device 420 to acquire the display image of the display unit 416 of the peripheral device 410. In step S704, the management device 450 determines whether or not there is another peripheral device 410 connected to the subsequent device. If it is determined in step S704 that there is a subsequent device (YES), the process returns to step S703. On the other hand, if it is determined in step S704 that there is no other peripheral device 410 connected to the subsequent device (NO), the process proceeds to step S705. In step S705, the management device 450 links the display image of the display unit 416 of the peripheral device 410 acquired so far with the quality data. In step S706, the setting information and device status information are acquired from the display image of the display unit 416 acquired.

In step S707, the management device 450 determines whether the acquired numerical value is different from the previous value. Here, it is assumed that the previous numerical value is stored in the management device 450 and the monitoring device 420. If it is determined in step S707 that the value is the same as the previous numerical value (NO), the process ends in step S711. On the other hand, if it is determined in step 707 that the value is different from the previous numerical value (YES), the process branches to step S708.

In step S708, the management device 450 retains the extracted setting information and device status information. In step S709, the management device 450 determines whether the retained information exceeds the settable number. If it is determined in step S709 that the settable number has not been exceeded (NO), the process ends in step S711. On the other hand, if it is determined in step S509 that the settable number has been exceeded (YES), the process branches to step S710. In step S710, the management device 450 discards the oldest information and terminates the process in step S711.

Figure 26 is a diagram for explaining the retention and discarding process of extracted setting information in the 3D modeling system according to the fourth embodiment. As shown in Figure 26, the values of the items of the acquired setting information and device status information can be retained in the management device 450 or the monitoring device 420. Here, there are two retention forms, as shown in Figures 26(A) and 26(B). The form shown in Figure 26(A) is for retaining all setting information and device information together with the date and time if the value of any one item of the setting information and device status information held by the peripheral device 410 is different from the previously saved value. In contrast, the form shown in Figure 26(B) is for retaining the value of each setting item (temperature is shown in Figure 26(B)) of the setting information and device status information held by the peripheral device 410 together with the date and time if the value is different from the previously saved value.

In the embodiment of FIG. 26(A), the information for each state of the peripheral device 410 can be known immediately, but if there is frequently changed setting information and device status information, the frequency of updates to the stored data increases, and the possibility of discarding the value you want to refer to increases. On the other hand, in the embodiment of FIG. 26(B), since the setting information and device status information are stored for each item, it is necessary to check the date and time of each data to confirm the information for each state of the peripheral device 410, which is time-consuming. On the other hand, there is an advantage that even if there is a setting value that is frequently updated, it is more likely that the value can be stored without being affected. Which of the above embodiments is used, and the number that can be stored can be changed depending on the system performance (e.g., storage area capacity, acquisition speed, etc.) and user settings. This makes it possible to store multiple values by determining the number that can be stored by the device specifications or user settings.

In this way, the management unit 452 includes a judgment unit that judges whether the acquired setting information and device status information have been changed. If the management unit 452 judges that the information has been changed, it manages the changed setting information and device status information together with the setting information and device status information that it holds. Being able to acquire the changed difference makes it easier to identify the cause of quality abnormalities. Note that this is not limited to the difference, and only the final image may be held.

According to the 3D modeling system 400 according to the fourth embodiment described above, even when it is difficult to obtain the information required for analysis by incorporating it into a log or the like, it is possible to obtain device status information and setting value information of the peripheral device 410 as quality data. This makes it possible to obtain setting information of the operation unit and analyze the cause of quality defects. By obtaining the display screens of multiple connected peripheral devices 410 and extracting the information, it is possible to obtain the information required for analysis even for devices whose information cannot be obtained from a log or devices that are not connected via a network.

In the 3D modeling system 400 according to the fourth embodiment described above, a management device 450 is provided to which quality information output from the 3D modeling device 110 is input, and the display screen of the display unit 416 of the peripheral device 410 and information extracted therefrom are collected and managed in the management device 450. In other words, in the fourth embodiment, the management device 450 includes an acquisition unit that collects information from multiple peripheral devices 410 and monitoring devices 420 and a management unit that manages the acquired information.

On the other hand, in other embodiments, it is also possible to manage the quality data by linking it to the display screen and the information extracted therefrom, without providing a separate management device 450. Below, with reference to FIG. 27 and again to FIG. 20, we will explain a three-dimensional modeling system 600 according to a fifth embodiment in which a separate management device 450 is not provided.

The fifth embodiment shown in FIG. 27 is a case where there is no management device, and the processing that was performed by the management device 450 is performed by a monitoring device. As shown in FIG. 27, the 3D modeling system 600 includes a 3D modeling device 110 that models a 3D object, one or more peripheral devices 610A, 610B, and one or more monitoring devices 620A, 620B provided for each peripheral device 610.

The 3D modeling device 110 receives data for forming a desired 3D object, and forms the 3D object based on the data. The peripheral devices 610 are devices connected downstream of the 3D modeling device 110, and are devices that further process the products generated by the 3D modeling device 110. The 3D modeling device 110 and the peripheral devices 610 are connected via an appropriate transport path, and the products of the 3D modeling device 110 are delivered to each peripheral device 610 via the transport path.

In the embodiment described, the 3D modeling system 600 further includes monitoring devices 620A and 420B provided for each peripheral device 610. The 3D modeling device 110 and the monitoring device 620 are connected via a wired or wireless connection or a network.

The 3D modeling device 110 acquires input data, setting information, and device status information (1), and notifies the acquired information to the monitoring device 620A of the subsequent peripheral device 610A (2). The monitoring device 620A acquires an image of the display unit of the corresponding peripheral device 610A (3), adds the information contained therein to the quality data received from the 3D modeling device 110, and transmits it to the subsequent monitoring device 620B (4). The subsequent monitoring device 620B acquires an image of the display unit of the peripheral device 610B corresponding to itself, and adds further information to the quality data to which the information acquired from the corresponding peripheral device 410 by one or more previous monitoring devices 620 has been added (3), and manages it.

By repeating this process, the last monitoring device 620 (620B in the example in FIG. 27) collects information from the monitoring devices 620A, 620B of the peripheral devices 610A, 610B connected to the 3D modeling device 110. The last monitoring device 620 links the acquired information with the quality data acquired from the 3D modeling device 110, and stores and manages it.

In FIG. 20, the configuration of a three-dimensional modeling system according to the fifth embodiment is shown by dashed lines. The monitoring device 620 according to the fifth embodiment shown in FIG. 20 includes a monitoring management unit 626, a monitoring storage unit 628, and a monitoring comparison unit 630 in addition to a monitoring unit 622 and an acquisition unit 624. In the fifth embodiment, the management device 450 is not provided, and the monitoring device 620 acquires the setting information and device status information displayed on the display unit 616 of the peripheral device 610 as an image, extracts the setting information and device status information from the image, and transmits the acquired image data, setting information, and device status information to the monitoring unit 622 of the subsequent monitoring device 620.

In a configuration in which a management device is not present, the monitoring management unit 626 operates similarly to the management unit 452. The monitoring management unit 626 manages the images acquired by the acquisition unit 624 by linking them to quality data. Furthermore, if the monitoring management unit 626 is a monitoring device 620 connected to the last peripheral device 610, it also links the received setting information and device status information of other peripheral devices to the quality data and manages them together. The monitoring management unit 626 also links the quality data to a quality abnormality possibility flag depending on the results of the comparison made by the monitoring comparison unit 630 and manages them together.

In a configuration in which no management device exists, the monitoring storage unit 628 operates similarly to the storage unit 456. The monitoring storage unit 628 is a non-volatile memory, and in a configuration in which no management device exists, it holds information on the allowable range of values for each item of setting information and device status information.

In a configuration in which no management device exists, the monitoring comparison unit 630 operates similarly to the comparison unit 458, comparing the values of the items of setting information and device status information acquired by the acquisition unit 624 with the corresponding allowable ranges stored in the monitoring storage unit 628, and notifying the monitoring management unit 626 of the comparison results.

According to the fifth embodiment, even in a configuration without a management device, it is possible to retain and manage information on the display screen of a peripheral device by linking it to quality data.

In the fourth and fifth embodiments described above, by linking and collectively managing information from multiple peripheral devices, it is possible to improve the efficiency of analysis. In this case, as a method of collectively managing the information, it may be a method of managing the information using the management device 450 as in the fourth embodiment, or a method in which the monitoring devices 620 as edge devices mounted on or connected to the peripheral devices 610 transmit data to each other and the data is collected and stored in the last monitoring device 620 as in the fifth embodiment. In either method, it is possible to assist in the analysis of the cause of quality defects by acquiring the setting information and device status information of the display unit of the peripheral device and adding it to the quality data. In particular, it is possible to acquire the information necessary for analysis even from devices whose information cannot be acquired from logs or from devices that are not connected to a network.

The present embodiment has been described above. According to the above-described embodiment, it is possible to provide a data output device, a three-dimensional modeling system, and a data output method capable of outputting quality information of a three-dimensional object.

According to a preferred embodiment, the 3D modeling device is capable of collecting, storing, and providing quality data such as sensor data that allows for analysis of the cause when a quality defect in a modeled object is detected. The quality data can be output for quality assurance. Preferably, the multiple sensor data are recorded while maintaining a correspondence between the acquisition timing and local data of the input data used for modeling (each control code and each command or group of commands therein). This allows the 3D modeling device 110 to evaluate quality defects in the modeled object and output the evaluation results, as well as to perform a detailed analysis of the cause when a quality defect is detected.

The functions of each of the above-mentioned embodiments of the present invention can be realized by a device-executable program written in C, C++, C#, Java (registered trademark), etc., and the program of this embodiment can be stored and distributed on a device-readable recording medium such as a hard disk drive, CD-ROM, MO, DVD, flexible disk, EEPROM, EPROM, etc., and can also be transmitted over a network in a format that can be used by other devices.

Although the present invention has been described above with reference to an embodiment, the present invention is not limited to the above-mentioned embodiment, and as long as the function and effect of the present invention are achieved within the scope of the embodiment that a person skilled in the art can imagine, it is included in the scope of the present invention.

100...3D modeling system, 110...3D modeling device, 112...head, 114...modeling plate, 115...nozzle, 116...heat sink, 118...fan, 120...heating block, 122...cooling block, 150...information processing device, 170...server device, 202...3D model data, 204...control data, 211...storage unit, 212...system controller, 213...analysis unit 213, 214...quality data recording unit, 215...quality data output unit, 216...engine controller, 217...sensor information acquisition unit, 218...error determination unit, 219...quality data transmission unit, 220...nozzle temperature sensor, 222...motor current sensor, 224 ...Motor speed detection sensor, 226...Filament supply unit, 228...Heater drive unit, 229...Heater, 230...Plate drive unit, 232...Head drive unit, 234...Imaging device, 236...3D measurement device, 252...Slicer software, 400, 600...3D modeling system, 410, 610...Peripheral equipment, 412, 612...Input unit, 414, 614...Control unit, 416, 616...Display unit, 420, 620...Monitoring device, 422, 622...Monitoring unit, 424, 624...Acquisition unit, 450...Management device, 452...Management unit, 454...Acquisition unit, 456...Storage unit, 458...Comparison unit, 626...Monitoring management unit, 628...Management storage unit, 630...Monitoring comparison unit

International Publication No. 2017/163432

Claims (21)

An acquisition means for acquiring predetermined information for three-dimensional modeling;
an analysis means for analyzing the predetermined information acquired by the acquisition means and judging whether or not the quality of the three-dimensional object obtained by the three-dimensional modeling is acceptable;
A determination means for determining an error based on the predetermined information acquired by the acquisition means;
and an output unit that outputs quality information of the three-dimensional object obtained by the three-dimensional modeling based on the predetermined information ,
the quality information includes a result of a judgment as to whether the quality of the three-dimensional object obtained by the three-dimensional modeling is acceptable or not,
The analysis by the analysis means is based on longer-term information and includes more complicated analysis processing compared to the error determination by the determination means.
Data output device. The data output device according to claim 1 , wherein the pass/fail quality of the three-dimensional object includes an evaluation of the quality of the entire three-dimensional object, one or more parts constituting the three-dimensional object, or a combination thereof. The predetermined information includes measurement information measured by a measuring means when a three-dimensional object is formed based on input data, and the measurement information is recorded in association with a portion of the input data.
3. The data output device according to claim 1. 4. The data output device according to claim 3, wherein the specified information includes at least one selected from the group consisting of error information based on measurement information measured by the measuring means during modeling, setting information for the three-dimensional modeling, device status information during modeling, image information obtained by photographing the modeled object during modeling, and three-dimensional measurement information obtained by three -dimensionally measuring the modeled object during modeling. The data output device according to claim 3 or 4, wherein the measurement information includes at least one measurement value selected from the group consisting of the current of one or more motors equipped in a three-dimensional modeling device performing the three-dimensional modeling, the speed of one or more motors equipped in the three-dimensional modeling device, and the temperature of one or more parts of the three-dimensional modeling device. An acquisition means for acquiring predetermined information for three-dimensional modeling;
an output unit that outputs quality information of the three-dimensional object obtained by the three-dimensional modeling based on the predetermined information;
Including,
the predetermined information includes measurement information measured by a measuring means when three-dimensional modeling is performed based on input data, the measurement information being recorded in association with a portion of the input data;
A data output device, wherein the association between the measurement information and the portion of the input data is based on time, time relative to a predetermined point in time in the three-dimensional modeling , or information indicating a correspondence between the measurement information and the portion of the input data. 7. The data output device according to claim 1, wherein the output means outputs the predetermined information together with the quality information. The data output device according to any one of claims 1 to 7 , further comprising a transmitting means for transmitting the predetermined information to an external device. A three-dimensional modeling means for executing three-dimensional modeling based on input data;
An acquisition means for acquiring predetermined information during the three-dimensional modeling;
an analysis means for analyzing the predetermined information acquired by the acquisition means and judging whether or not the quality of the three-dimensional object obtained by the three-dimensional modeling is acceptable;
A determination means for determining an error based on the predetermined information acquired by the acquisition means;
and an output unit that outputs quality information of the three-dimensional object obtained by the three-dimensional modeling based on the predetermined information ,
the quality information includes a result of a judgment as to whether the quality of the three-dimensional object obtained by the three-dimensional modeling is acceptable or not,
The analysis by the analysis means is based on longer-term information and includes more complicated analysis processing compared to the error determination by the determination means.
Three-dimensional modeling system. The three-dimensional printing system according to claim 9, further comprising a monitoring unit that monitors an apparatus that performs processing during or after the three-dimensional printing, and acquires information displayed on a display unit of the apparatus that performs processing during or after the three - dimensional printing as an image. an acquisition unit that acquires information displayed on a display unit of an apparatus performing processing during or after the three-dimensional modeling from the monitoring unit;
The three-dimensional object fabrication system according to claim 10 , further comprising: a management unit that manages the information acquired by the acquisition unit. The three-dimensional printing system according to claim 11, wherein the monitoring unit is provided for one or more devices that perform processing during or after three-dimensional printing , the acquisition unit acquires information acquired by one or more of the monitoring units, the management unit manages the information acquired from the one or more monitoring units, and the acquired information is added to input data when performing three-dimensional printing and recorded. The three-dimensional modeling system of claim 12, further comprising an extraction unit that extracts at least one of setting information and device status information from the image acquired by the monitoring unit, and the input data is supplemented with at least one of the setting information and device status information extracted from the image and the image, or either one of these. a determination unit that determines whether or not at least one of the setting information and the device status information acquired by the extraction unit has been changed;
The three-dimensional modeling system according to claim 13, wherein when the judgment unit determines that the setting information and device status information have been changed, the management unit manages at least one of the changed setting information and device status information together with the setting information and device status information that it holds. The three - dimensional object fabrication system according to claim 13 , wherein the management unit further manages a maximum number of at least one of the setting information and the apparatus status information that can be stored. a storage unit for storing a tolerance range for each item of at least one of the setting information and the device status information;
A three-dimensional modeling system according to any one of claims 13 to 15, further comprising: a comparison unit that compares the allowable range with the value of at least one of the items of the corresponding setting information and the device status information, and if the result of the comparison unit shows that the input data is outside the allowable range , a quality abnormality possibility flag is linked to the input data. The three-dimensional printing system according to claim 16, wherein the comparison unit further compares the acceptable range with the value of at least one of the items of the corresponding setting information or device status information when a new acceptable range for at least one of the items of the corresponding setting information or device status information is stored in the storage unit . a management device to which the quality information output by the output means is input, the management device including the acquisition unit and the management unit;
and one or more monitoring devices each having the monitoring unit for monitoring a device performing a process during or after the corresponding three - dimensional modeling . The three-dimensional modeling system according to any one of claims 12 to 17, further comprising one or more monitoring devices each equipped with the monitoring unit for monitoring an apparatus performing a corresponding process during or after the three-dimensional modeling , wherein one of the one or more monitoring devices receives an input of the quality information output by the output means, adds to the quality information information information displayed on a display unit of the apparatus performing the corresponding process during or after the three -dimensional modeling, and outputs the quality information with the added information to a subsequent stage, wherein a subsequent one of the one or more monitoring devices receives an input of the quality information with the added information, further adds to the quality information information displayed on a display unit of the apparatus performing the corresponding process during or after the three-dimensional modeling, and outputs the quality information with the added information to a subsequent stage, wherein a subsequent one of the one or more monitoring devices is equipped with the acquisition unit and the management unit. An apparatus for receiving the quality information from the data output apparatus according to any one of claims 1 to 8 ,
an acquisition unit that acquires information displayed on a display unit of an apparatus performing a process during or after the three-dimensional modeling, the information being acquired as an image by a monitoring unit that monitors the apparatus performing a process during or after the three-dimensional modeling ;
a management unit that manages the information acquired by the acquisition unit. The computer
A step of acquiring predetermined information for three-dimensional modeling;
a step of analyzing the predetermined information acquired in the acquiring step and determining whether or not the quality of the three-dimensional object obtained by the three-dimensional modeling is acceptable;
performing an error determination based on the predetermined information acquired in the acquiring step;
and outputting quality information of the three-dimensional object obtained by the three-dimensional modeling based on the predetermined information .
the quality information includes a result of a judgment as to whether the quality of the three-dimensional object obtained by the three-dimensional modeling is acceptable or not,
The analysis in the determining step is based on longer-term information and includes a more complicated analysis process than the error determination in the error determination step.
Data output method.