KR102262058B1 - Method for setting of process optimazation of three-dimensional printer - Google Patents

Abstract

The present invention relates to a process optimization setting method of a 3D printer of a laser melting method, and the process optimization setting method of a 3D printer according to an embodiment of the present invention includes a process setting value including a target density of the 3D printer establishing a data according to the results of the first filtering and the second filtering in which filtering conditions are set differently according to the target density by setting variable sections of the set process, the first filtering result and the second filtering 2 If the filtering results are the same, the method may include excluding a process outside a preset error range, and setting a setting process excluding the error range as an optimization process.

Description

How to set process optimization of 3D printer {METHOD FOR SETTING OF PROCESS OPTIMAZATION OF THREE-DIMENSIONAL PRINTER}

The present invention relates to a method for setting process optimization of a laser melting type 3D printer.

In general, a 3D printer is widely used in the metal field because it is possible to manufacture precise and complex products.

In such a 3D printer, metal powder is discharged on the base plate and melts specific points with a laser, but melting and solidification times in a local range are short, so problems such as pore molding and unmelting may occur.

In the prior art, defects were evaluated using variables such as scan speed, laser power, and stacking thickness according to the type of powder and device, but a method capable of optimizing the process is needed.

Republic of Korea Patent Publication No. 10-2019-0058955

According to an embodiment of the present invention, there is provided a process optimization setting method of a laser melting type 3D printer.

In order to solve the problems of the present invention described above, the method for setting process optimization of a 3D printer according to an embodiment of the present invention includes the steps of setting a process setting value including a target density of the 3D printer, a set process variable Building data according to the results of the first filtering and the second filtering in which filtering conditions are set differently according to the target density by setting a section, and when the first filtering result and the second filtering result are the same, preset It may include excluding a process outside the error range, and setting a setting process from which the error range is excluded as an optimization process.

According to an embodiment of the present invention, the number of iterations for process optimization can be reduced, and the development cost for developing an optimal process can be reduced, and there is an effect that can be done.

1 is a schematic configuration diagram of an apparatus for setting process optimization of a 3D printer according to an embodiment of the present invention.
2 is a schematic flowchart of a process optimization setting method of a 3D printer according to an embodiment of the present invention.
3 is a schematic flowchart of a database construction step of a process optimization setting method of a 3D printer according to an embodiment of the present invention.
4 is a schematic flowchart of the first filtering step of the database building step of the process optimization setting method of the 3D printer according to an embodiment of the present invention.
5 is a schematic flowchart of the second filtering step of the database building step of the process optimization setting method of the 3D printer according to an embodiment of the present invention.
6A, 6B, and 6C are graphs illustrating the optimal process progress extracted to the optimal region according to the process optimization setting method of the 3D printer according to an embodiment of the present invention.
7 is a diagram illustrating an example computing environment in which one or more embodiments disclosed herein may be implemented.

Hereinafter, preferred embodiments will be described in detail so that those of ordinary skill in the art can easily practice the present invention with reference to the accompanying drawings.

1 is a schematic configuration diagram of an apparatus for setting process optimization of a 3D printer according to an embodiment of the present invention.

Referring to FIG. 1 , an apparatus 100 for setting process optimization of a 3D printer according to an embodiment of the present invention may optimize a process of the 3D printer 10 .

To this end, the process optimization setting apparatus 100 of the 3D printer may include a setting unit 110 and a process optimization unit 120 .

The setting unit 110 may receive a target density of the powder stacked by the 3D printer, and in addition, equipment information such as the type of the 3D printer, the laser irradiation type, and the powder manufacturer of the 3D printer, the type of powder metal, etc. You can receive more powder information.

The process optimization unit 120 may automatically analyze the information from the setting unit 110 to build a database, and may set the remaining data as an optimization process, except for a process within a preset error range among the filtered data. For the automatic analysis and database construction described above, various techniques such as machine learning, deep learning, artificial intelligence, and artificial neural networks may be used.

2 is a schematic flowchart of a process optimization setting method of a 3D printer according to an embodiment of the present invention.

1 and 2, in the process optimization setting method of the 3D printer according to an embodiment of the present invention, the setting unit 110 may receive a target density of the powder stacked by the 3D printer, In addition, equipment information such as the type of the 3D printer and the laser irradiation type, and powder information such as the powder manufacturer and the type of powder metal of the 3D printer may be further input (S1).

Thereafter, the process optimization unit 120 sets a variable section of the set process to construct data according to the results of the first filtering and the second filtering in which filtering conditions are set differently according to the target density (S2), and the second If the first filtering result and the second filtering result are the same, the process of the preset error range may be excluded (S3), and the setting process excluded from the error range may be set as the optimization process (S4).

3 is a schematic flowchart of a database construction step of a process optimization setting method of a 3D printer according to an embodiment of the present invention.

Referring to FIG. 3 together with FIGS. 1 and 2 , the process optimization unit 120 sets a variable section of the set process and sets different filtering conditions according to the target density according to the results of the first filtering and the second filtering. In constructing data according to (S2), setting a variable section (21), setting a first relational expression between variables of the set variable section (S22), a laser beam diameter of a 3D printer and scanning of the laser beam Measuring an overlap distance (S23), measuring a unit energy density (VED) according to the first relational expression (S24), a unit energy density higher than the target density in a preset first range A first filtering step (S25) of filtering the process settings having the same, and a second filtering step (S26) of filtering the process settings having a unit energy density higher than the target density among a preset second range may be performed.

The first relation between the variables is

Here, VED is a unit energy density, P is laser power, v is a laser beam scan speed of the 3D printer, σ is a laser beam diameter of the 3D printer, and t is a thickness of powder stacked in the 3D printer.

4 is a schematic flowchart of the first filtering step of the database building step of the process optimization setting method of the 3D printer according to an embodiment of the present invention.

Referring to FIG. 4 , the first filtering step ( S25 ) includes obtaining a unit energy density corrected according to a second relational expression set in advance ( S251 ), and setting a first filtering range according to the corrected unit energy density ( S251 ). S252, S253, S254, S255, S256, S257, S258), and storing data within the first filtering range (S259).

The second relational expression (MVED') between the variables is a relation obtained by calculating the overlapping interval of laser scans and the size of the laser beam in order to correct the unit energy density of the first relational expression and multiplying it by an exponential function proportional to a constant of a certain size. . The above-described second relational expression applies only when the laser scan overlapping interval is smaller than the size of the laser beam, and the above-described second relational expression may also include a correction value for the size of the laser beam that is distorted through the lens and formed in the powder. have.

The step of setting the first filtering range according to the corrected unit energy density is setting the first filtering range according to the corrected unit energy density (S252, S253, S254), and is set according to the density and the target density in the set range. The reference value C1 is compared (S256, S258) and the range is updated according to the result (S255, S257), and the number in which the density in the updated range is higher than the reference value C1 set according to the target density is less than the number lower It is possible to store (S259) the data of the multi-faceted updated range.

Referring to FIG. 4 , in the step of setting the first filtering range, the constant K to be used for the first filtering may vary depending on the type of equipment, the type of powder, the process variable, etc., and each has an optimal constant. The range of the constant has a magnitude greater than 0.6 and less than 1. In the first optimal process, an arbitrary constant is used as the basis. The arbitrary constant is set as a constant that can be obtained in the range of the minimum density and the maximum density in the VED range having a target density or more. It allows the user to use similar data as a basis for repeated execution rather than the first execution, and the constant K can be arbitrarily set by the user and used.

5 is a schematic flowchart of the second filtering step of the database building step of the process optimization setting method of the 3D printer according to an embodiment of the present invention.

Referring to FIG. 5 , the second filtering step (S26) is a step of receiving the final data of the first filtering step (S261), and obtaining a second-corrected unit energy density according to a third relational expression (S262). , setting a second filtering range according to the second corrected unit energy density (263, S264, S265, S266, S267, S268), and storing data within the second filtering range (S269). have.

The third relational expression (AMVED'') on the variable is the output laser power of the 3D printer, the energy power of the powder surface formed by the lens in real time, and the constant set to correct the size of the laser beam. This is a relational expression in which the energy density obtained by multiplying the corrected energy density obtained by the relational expression is calculated as the unit movement speed or acceleration of the laser scan area in the range that acts locally.

In the step of setting the second filtering range according to the corrected unit energy density, the second filtering range is set according to the corrected unit energy density (S263, S264), and a reference value set according to the density in the set range and the target density ( C2) is compared (S266, S268) and the range is updated according to the result (S265, S267), and if the number in the updated range is higher than the reference value (C1) set according to the target density is less than the lower number, it is updated It is possible to store (S269) the data of the specified range.

The constants obtained from the above-mentioned second and third relational expressions can be changed by performing experimental iterations, machine learning deep learning, artificial intelligence, regression analysis through artificial neural networks, etc., and equipment input by the user during repetitive work; It can be changed and used according to the setting of powder and parameters.

The filtering ranges (S255, S257, S265, S267) used in FIGS. 4 and 5 can be changed, and the finer the filter, the more accurate the filtering result can be obtained, so it can be adjusted according to the amount of input data and the performance of the computing device and system used. .

6A, 6B, and 6C are graphs showing the optimal process progress extracted to the optimal region according to the process optimization setting method of the 3D printer according to an embodiment of the present invention.

Referring to FIG. 6A , you can see the unit energy density graph of each process according to the first relational expression, and referring to FIG. 6B , you can see the corrected unit energy density graph of each process by the first filtering step S25. 6c, the secondly corrected unit energy density graph of each process by the second filtering step (S26) can be seen.

7 is a diagram illustrating an example computing environment in which one or more embodiments disclosed herein may be implemented, an illustration of a system 1000 including a computing device 1100 configured to implement one or more embodiments described above. shows For example, computing device 1100 may be a personal computer, server computer, handheld or laptop device, mobile device (mobile phone, PDA, media player, etc.), multiprocessor system, consumer electronics, minicomputer, mainframe computer, distributed computing environments including any of the aforementioned systems or devices, and the like.

The computing device 1100 may include at least one processing unit 1110 and a memory 1120 . Here, the processing unit 1110 may include, for example, a central processing unit (CPU), a graphic processing unit (GPU), a microprocessor, an Application Specific Integrated Circuit (ASIC), Field Programmable Gate Arrays (FPGA), etc. and may have a plurality of cores. The memory 1120 may be a volatile memory (eg, RAM, etc.), a non-volatile memory (eg, ROM, flash memory, etc.), or a combination thereof.

Additionally, computing device 1100 may include additional storage 1130 . Storage 1130 includes, but is not limited to, magnetic storage, optical storage, and the like. The storage 1130 may store computer readable instructions for implementing one or more embodiments disclosed herein, and other computer readable instructions for implementing an operating system, an application program, and the like. Computer readable instructions stored in storage 1130 may be loaded into memory 1120 for execution by processing unit 1110 .

Computing device 1100 may also include input device(s) 1140 and output device(s) 1150 . Here, the input device(s) 1140 may include, for example, a keyboard, mouse, pen, voice input device, touch input device, infrared camera, video input device, or any other input device, or the like. Further, the output device(s) 1150 may include, for example, one or more displays, speakers, printers, or any other output device, or the like. Also, the computing device 1100 may use an input device or an output device included in another computing device as the input device(s) 1140 or the output device(s) 1150 .

In addition, the computing device 1100 may include communication connection(s) 1160 that enable it to communicate with another device (eg, the computing device 1300 ) over the network 1200 . Here, communication connection(s) 1160 may be a modem, network interface card (NIC), integrated network interface, radio frequency transmitter/receiver, infrared port, USB connection, or other for connecting computing device 1100 to another computing device. It may include interfaces. Also, the communication connection(s) 1160 may include a wired connection or a wireless connection.

Each component of the above-described computing device 1100 may be connected by various interconnections such as a bus (eg, peripheral component interconnection (PCI), USB, firmware (IEEE 1394), optical bus structure, etc.) and may be interconnected by a network.

As used herein, terms such as "configuration unit", "process optimization unit" and the like generally refer to a computer-related entity that is hardware, a combination of hardware and software, software, or software in execution. For example, a component can be, but is not limited to being, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, and/or a computer. For example, both an application running on a controller and a controller may be a component. One or more components may reside within a process and/or thread of execution, and components may be localized on one computer or distributed between two or more computers.

As described above, according to the present invention, the detection rate of a high-density process can be improved to ensure the soundness of metal products, and the number of iterations for process optimization can be reduced by reducing the number of maximum error values as shown in FIGS. 6A to 6C . It can reduce the development cost of developing an optimal process when the internal conditions of new powder and metal 3D printing equipment are changed, and even in the case of the same powder in the same equipment, when the process of optimizing is necessary when installed in a new place, many repetitions It must be verified through work, but time can be reduced for an algorithm that provides a guide to the optimal process.

The present invention described above is not limited by the above-described embodiments and the accompanying drawings, but is limited by the claims described below, and the configuration of the present invention may vary within the scope without departing from the technical spirit of the present invention. Those of ordinary skill in the art to which the present invention pertains can easily recognize that the present invention can be changed and modified.

100: 3D printer process optimization setting
110: setting unit
120: process optimization unit

Claims (8)

setting a process setting value including a target density of the 3D printer;
constructing data according to the results of the first filtering and the second filtering in which filtering conditions are set differently according to the target density by setting variable sections of the set process;
excluding a process outside a preset error range among processes of a 3D printer when the first filtering result and the second filtering result are the same; and
Setting a process within the error range among the processes of the 3D printer as an optimization process
Process optimization setting method of a 3D printer comprising a.
According to claim 1,
The process setting value is a process optimization setting method of a 3D printer for further setting laser printer equipment information and powder information.
According to claim 1,
Building the data is
setting a variable section;
setting a first relational expression between variables of a set variable section;
Measuring the laser beam diameter of the 3D printer and the scan overlapping distance of the laser beam
measuring a volume energy density (VED) according to the first relational expression;
a first filtering step of filtering a process setting having a unit energy density higher than the target density among a first preset range; and
A second filtering step of filtering a process setting having a unit energy density higher than the target density among a second preset range
including,
The first relation between the variables is

where VED is the unit energy density, P is the energy density, v is the laser beam scan speed of the 3D printer, σ is the laser beam diameter of the 3D printer, and t is the thickness of the powder stacked in the 3D printer. How to set up optimization.
delete 4. The method of claim 3,
The first filtering step is
Obtaining a corrected unit energy density for correcting the unit energy density of the first relational expression by multiplying the first relational expression by an exponential function proportional to a constant of a certain size based on the overlapping interval of the laser beam scan and the size of the laser beam step;
setting a first filtering range according to the corrected unit energy density; and
Storing data within the first filtering range
Process optimization setting method of a 3D printer comprising a.
delete 6. The method of claim 5,
The second filtering step is
A constant set to correct the output laser power of the 3D printer, the energy power of the powder surface formed by the lens in real time, and the size of the laser beam by receiving the final data of the first filtering step as the input to the corrected unit energy density calculating the secondly corrected unit energy density by calculating the energy density obtained by multiplying it as one of the unit moving speed or the acceleration of the laser scan area in the range of locally acting;
setting a second filtering range according to the second corrected unit energy density; and
and storing data within the second filtering range. delete

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