JP7391718B2 - A method for predicting the material quality of an additively manufactured product, a method for constructing a material database, a layer planning method for an additively manufactured product, and a method for manufacturing an additively manufactured product - Google Patents

Description

The present invention relates to a method for predicting material properties of a laminate-produced product, a method for constructing a material database, a layer planning method for a laminate-produced product, and a method for manufacturing a laminate-produced product.

Mechanical strength evaluation is indispensable in order to increase the reliability of additively manufactured products formed by laminating welded beads. In particular, tensile strength is the most basic strength characteristic and is widely used as an evaluation standard.
The tensile strength of the laminate structure can be measured using a test piece cut out from the laminate structure after modeling. However, in that case, it was necessary to produce a plurality of layered products, which was not necessarily efficient.
Generally, the tensile strength of a material is higher as the crystal grain size (grain size) of the material structure is smaller, so if the crystal grain size can be determined, the tensile strength of the material can be predicted without actually manufacturing the additively manufactured object. Therefore, by determining the grain size of the material structure in advance, there is a technology that predicts the material quality of an additively manufactured object based on the relationship between the material structure and the material properties such as tensile strength, without actually manufacturing the object. It is disclosed in Patent Document 1.

Japanese Patent Application Publication No. 2004-4034

However, in order to predict the material quality after manufacturing, the calculation process is complicated and enormous when analyzed from the principles and principles, so it is not practical to apply to parts manufacturing using additive manufacturing. Therefore, it may be possible to create a database of existing experience information and predict material properties based on this database. However, methods that utilize databases have the following drawbacks.
First, the existing continuous cooling transformation diagram (CCT diagram) for welding is for welding a single layer, and there is no database that corresponds to the reheated structure when welding multiple layers. .
It is also possible to investigate by changing the reheating conditions using a transformation point measuring device (processing formaster) that can measure the transformation point after processing, but in that case, it is necessary to consider at least two passes of transformation. . For this reason, the conditions vary widely, making it difficult to predict the material.

As described above, for a laminate-produced product in which welded beads are laminated in multiple layers, prediction of the material requires extremely complicated processing and requires time-consuming work.

Therefore, the present invention provides a material database for additively manufactured objects that can accurately predict the material properties of additively manufactured objects using a material database that correlates material information of actually manufactured objects with the results of temperature analysis under the same manufacturing conditions. A prediction method, a construction method of a material database that efficiently constructs the material database, and a material database that can be used to accurately predict the material of an additively manufactured object, and that can produce an additively manufactured object with desired material properties. It is an object of the present invention to provide a layer planning method for a laminate-produced product that can be stably manufactured, and a method for manufacturing a laminate-produced product.

The present invention consists of the following configuration.
(1) A method for predicting the material quality of an additively manufactured product in which welded beads made by melting and solidifying a filler material are laminated, the method comprising:
acquiring a temperature history profile representing a temperature change of a specific weld bead during formation of the weld bead of the laminate-molded object;
extracting a plurality of local maximum points in the temperature history profile that are included in a test temperature range that is below the melting point of the weld bead and above the transformation point of the weld bead;
The material information corresponding to the extracted temperature combination of the maximum points is extracted by referring to a material database in which material information of the welding bead corresponding to the temperature of the maximum point is associated in advance, and the material information is applied to the welding bead. A process of outputting as a bead material prediction result,
A method for predicting material properties of additively manufactured objects.
(2) A method for constructing a material database having data elements representing the relationship between material information of a laminate-produced product in which welded beads obtained by melting and solidifying filler metal and the temperature history of the welded beads, the method comprising:
generating a temperature history profile representing a temperature change of a specific weld bead during formation of the weld bead of the laminate-molded object by computer simulation;
extracting a plurality of local maximum points in the temperature history profile that are included in a test temperature range that is below the melting point of the weld bead and above the transformation point of the weld bead;
storing the data element that associates the material information of the weld bead formed by the temperature history profile with the combination of temperatures of the plurality of local maximum points;
How to build a material database including:
(3) A layer planning method for a layered product in which welded beads made by melting and solidifying a filler material are layered, the method comprising:
A first step of predicting the material of the welded bead constituting the laminate-molded article by the method for predicting the material quality of the laminate-molded article according to (1);
If the prediction result of the material in the first step does not satisfy the preset required material characteristics of the weld bead, the amount of heat input applied to the formation of the weld bead is changed, and the weld bead is formed with the changed amount of heat input. a second step of predicting the material of the welding bead again using the material prediction method of the laminate-molded object;
has
A laminate planning method for a laminate-molded article, wherein the second step is repeated until the prediction result of the material in the second step satisfies the required material characteristics.
(4) A layer planning method for a layered product in which welded beads made by melting and solidifying a filler material are layered, the method comprising:
A first step of predicting the material of the welded bead constituting the laminate-molded article by the method for predicting the material quality of the laminate-molded article according to (1);
If the prediction result of the material in the first step does not satisfy the preset required material characteristics of the weld bead, the type of the filler metal is changed, and the weld bead is formed with the changed filler metal. a second step of predicting the material of the layer again using the material prediction method of the laminate-molded object;
has
A laminate planning method for a laminate-molded article, wherein the second step is repeated until the prediction result of the material in the second step satisfies the required material characteristics.
(5) A layer planning method for a layered product in which welded beads made by melting and solidifying a filler material are layered, the method comprising:
a filler material selection step of determining a recommended filler material to be used in the layered product by referring to a material database including material information of the welding bead;
The material database includes an inspection of a temperature history profile representing a temperature change of a specific weld bead at a temperature below the melting point of the weld bead and above the transformation point of the weld bead during formation of the weld bead of the laminate-molded object. Having material information of the weld bead corresponding to a combination of temperatures of a plurality of local maximum points included in the temperature range for each type of the filler metal,
In the filler metal selection process,
Searching from the material information in the material database for a target material that satisfies the required material characteristics of the weld bead and constraints on the bead shape when forming the weld bead;
If the material information corresponding to the target material can be detected, determining the type of filler metal corresponding to the material information as the recommended filler material to be used;
Laminate planning method for additively manufactured objects.
(6) A method for manufacturing a laminate-manufactured object, comprising manufacturing the laminate-manufactured object in accordance with the procedure of the laminate-planning method according to (5).

According to the present invention, it is possible to accurately predict the material of a layered product using a material database that associates material information of an actually manufactured layered product with results of temperature analysis under the same manufacturing conditions. Additionally, a material database can be constructed efficiently. Furthermore, the obtained material database can be used to accurately predict the material of the laminate-molded object, and the laminate-molded object having desired material properties can be stably manufactured.

FIG. 1 is a schematic diagram of a layered manufacturing apparatus that operates based on the method for manufacturing a layered product according to the present invention. Figure 2 is an explanation that schematically shows the construction of a material database for predicting the material quality of an additively manufactured object, the creation of a lamination plan using this material database, the creation of a modeling program, and each processing procedure of additive manufacturing. It is a diagram. FIG. 3 is a flowchart showing the procedure for constructing and outputting a material database. FIG. 4 is an explanatory diagram schematically showing the correspondence between the material information measured from the formed weld bead and the temperature history profile obtained by simulation. FIG. 5 is a graph showing a specific example of a simulated temperature history profile. FIG. 6 is an explanatory diagram showing a specific example of data elements to be registered in the material database. Figure 7 is a graph showing the difference in cooling characteristics when beads are formed with different amounts of heat input. It is a graph showing temperature change characteristics in the case of heat amount. FIG. 8 is a flowchart showing the steps of the first layer planning method that satisfies the required material properties. FIG. 9 is a flowchart showing the steps of a third layer planning method that satisfies required material properties.

Embodiments of the present invention will be described in detail below with reference to the drawings.
In the method for manufacturing a laminate-manufactured object according to the present invention, the material quality of the laminate-manufactured object is predicted using a material database prepared in advance, so that the laminate-manufactured object after manufacturing has desired material properties. Perform stacking planning.
First, the structure of a layered manufacturing apparatus for manufacturing a layered object will be described.
<Additive manufacturing equipment>
FIG. 1 is a schematic diagram of a layered manufacturing apparatus that operates based on the method for manufacturing a layered product according to the present invention.
The layered manufacturing apparatus 100 includes a modeling section 11, a controller 13 that centrally controls the modeling section 11, and a power supply device 15.

(modeling department)
The modeling section 11 includes a welding robot 19 having a torch 17 on its tip shaft, and a filler material supply section 21 that supplies filler material (welding wire) M to the torch 17.

The welding robot 19 is an articulated robot, and a torch 17 is supported on the tip shaft of the robot arm so that the filler metal M can be continuously supplied. The position and orientation of the torch 17 can be arbitrarily set three-dimensionally within the degree of freedom of the robot arm.

The torch 17 holds the filler metal M and generates an arc from the tip of the filler metal M in a shielding gas atmosphere. The torch 17 has a shield nozzle (not shown), and shield gas is supplied from the shield nozzle. The arc welding method may be a consumable electrode method such as coated arc welding or carbon dioxide arc welding, or a non-consumable electrode method such as TIG welding or plasma arc welding, and the method may be selected as appropriate depending on the layered product to be manufactured. Ru.

For example, in the case of a consumable electrode type, a contact tip is arranged inside the shield nozzle, and the filler material M to which melting current is supplied is held in the contact tip.

The filler metal M is fed from the filler metal supply section 21 to the torch 17 by a feeding mechanism (not shown) attached to the robot arm of the welding robot 19 or the like. The torch 17 is moved along a desired welding line by driving the robot arm according to a command from the controller 13. Further, the continuously fed filler metal M is melted and solidified in the shielding gas atmosphere by an arc generated at the tip of the torch 17. As a result, a weld bead B, which is a molten solidified body of the filler metal M, is formed. In this way, the modeling unit 11 is for laminating the molten metal of the filler metal M, and by laminating the weld beads B in a multilayered manner on the base plate 23, a layered product W having a desired shape is created. do.

The heat source for melting the filler metal M is not limited to the above-mentioned arc. For example, other types of heat sources may be used, such as a heating method using a combination of an arc and a laser, a heating method using plasma, a heating method using an electron beam or a laser, and the like. When using an arc, the weld bead B can be easily formed without depending on the material or structure while ensuring shielding properties. When heating with an electron beam or laser, the amount of heating can be controlled more precisely, the state of the weld bead B can be maintained more appropriately, and the quality of the laminate-molded product W can be further improved.

As the filler metal M, any commercially available welding wire can be used. For example, it is specified in MAG welding and MIG welding solid wire for mild steel, high tensile strength steel and low temperature steel (JIS Z 3312), arc welding flux cored wire for mild steel, high tensile strength steel and low temperature steel (JIS Z 3313), etc. wire can be used. Furthermore, by including appropriate additives in the filler metal, it is possible to impart functionality such as strengthening the weld bead.

(controller)
The controller 13 includes a layer planning section 31, a material prediction section 33, a determination section 35, a modeling program creation section 37, a storage section 39, and a control section 45 to which these sections are connected. The input section 41 and the output section 43 are connected to the control section 45 .

Three-dimensional shape data (CAD data, etc.) representing the shape of the layered product W to be manufactured and various instruction information are input to the control section 45 from the input section 41 . The output unit 43 outputs various types of information from the control unit 45, such as various drive control information and material database information to be described later, as needed.

The control unit 45 generates a shape model for bead formation using the input three-dimensional shape data, and creates a lamination plan including the movement trajectory of the torch 17 and welding conditions. Further, the control unit 45 creates a modeling program according to the lamination plan, and drives each part according to this modeling program to layer-manufacture a layered object W having a desired shape.

The layer planning unit 31 decomposes the shape model of the input three-dimensional shape data into a plurality of layers corresponding to the height of the weld bead B. Then, for each layer of the disassembled shape model, the trajectory of the torch 17 for forming the weld bead B and the heating conditions for forming the weld bead B (to obtain the welding current, desired bead width, bead stacking height, etc.) Create a stacking plan that defines the conditions (including the conditions for

The material prediction unit 33 predicts the material of the weld bead formed according to the lamination plan by referring to a material database prepared in advance. The determining unit 35 determines whether the predicted material of the weld bead falls within the allowable range of the required material characteristics, and if it exceeds the allowable range, instructs to change the conditions and perform the lamination plan again. Details of the material prediction section 33 and the determination section 35 will be described later.

The modeling program creation unit 37 drives each part of the modeling unit 11 to set a modeling procedure for the layered object W, and creates a modeling program that causes a computer to execute this procedure. The created modeling program is stored in the storage unit 39.

In addition to storing a modeling program and a material database described later, the storage unit 39 also stores specifications of various drive units included in the modeling unit 11, information on the material of the filler metal M, and the like. The stored information is appropriately referenced as needed when creating a modeling program in the modeling program creation section 37, when executing the modeling program, and the like. This storage unit 39 is made up of a storage medium such as a memory or a hard disk, and is capable of inputting and outputting various information.

The controller 13 including the control unit 45 is a computer device including a CPU, memory, I/O interface, and the like. The controller 13 has a function of reading data and programs stored in the storage section 39, processing the data and executing an operation program, and a function of driving and controlling each section of the modeling section 11. The control unit 45 creates a modeling program and executes the modeling program based on instructions from the input unit 41 through operations, communication, and the like.

When the control section 45 executes the modeling program, each section such as the welding robot 19 and the power supply device 15 is driven according to a predetermined programmed procedure. The welding robot 19 moves the torch 17 along a programmed trajectory according to a command from the controller 13, melts the filler metal M with an arc at a predetermined timing, and places a weld bead B at a desired position. Form.

The modeling program here is an instruction code for causing the modeling unit 11 to execute a procedure for forming the welding bead B designed by a predetermined calculation based on input three-dimensional shape data of the layered product W. The control unit 45 reads a desired lamination program from the storage unit 39 and executes it, thereby driving the modeling unit 11 and manufacturing the layered product W. That is, the control unit 45 moves the torch 17 by driving the welding robot 19 according to the modeling program, and generates an arc from the tip of the torch 17. Thereby, weld beads B are repeatedly formed on the base plate 23, and a laminate-molded article W is modeled.

Each calculation unit, such as the stacking planning unit 31, the material prediction unit 33, the determination unit 35, and the modeling program creation unit 37, is provided in the controller 13, but is not limited thereto. Although not shown, for example, the above-mentioned calculation unit may be provided in an external computer such as a server or a terminal that is placed separately from the additive manufacturing apparatus 100 via a communication means such as a network or a storage medium. Good too. By providing the above-mentioned calculation unit in the external computer, a desired modeling program can be created without requiring the additive manufacturing apparatus 100, and the program creation work does not become complicated. Further, by transferring the created modeling program to the storage unit 39 of the controller 13, the modeling unit 11 can be operated in the same way as when the operation program is created with the controller 13.

<Method for predicting material quality of additively manufactured objects>
Next, a method for predicting the material quality of an additively manufactured object will be described.
Figure 2 is an explanation that schematically shows the construction of a material database for predicting the material quality of an additively manufactured object, the creation of a lamination plan using this material database, the creation of a modeling program, and each processing procedure of additive manufacturing. It is a diagram.

First, a method for constructing a material database will be explained.
The material database has a large number of data elements representing the relationship between the material information of a laminate-molded product in which welded beads made by melting and solidifying filler metal are laminated, and the temperature history of the welded beads.

For example, the shape data of the layered product to be manufactured and the welding conditions for manufacturing the layered product are determined, and a layer plan, which is a procedure for forming weld beads for manufacturing the layered product, is created. Based on this lamination plan, a weld bead for evaluation is actually formed using the modeling section 11 shown in FIG. Furthermore, based on this lamination plan, the temperature history of the weld bead that is simulated to be formed is analytically determined by computer simulation.

On the other hand, the crystal grain size (for example, grain size) and hardness (for example, Vickers hardness) of the crystal structure at a specific position of the weld bead actually produced based on the above lamination plan are measured. These measurement results become material information. Furthermore, through the above simulation, a temperature history profile in which the temperature is repeatedly raised and lowered due to the formation of the weld bead at a specific position of the weld bead is determined. As a result, a data element 51 is obtained that includes the analytically determined temperature history profile at a specific position and information on the actually measured crystal grain size and hardness of the structure. By repeatedly generating data elements 51 obtained in this manner for a plurality of different locations of the weld bead, a material database DB including a large number of data elements 51 is constructed.

The material quality prediction unit 33 shown in FIG. Predict what kind of material (crystal grain size, hardness) the weld bead will be made of.

The determining unit 35 determines whether the material predicted by the material predicting unit 33 satisfies desired material properties. If the required material characteristics are satisfied, the modeling program creation unit 37 creates a modeling program based on the created stacking plan. If the required material characteristics are not satisfied, the modeling conditions are changed, for example by changing the heat input during welding or the filler metal, and the lamination plan is created again. Then, the material prediction unit 33 predicts the material of the weld bead based on the re-created lamination plan, and the determination unit 35 determines whether the material of the weld bead satisfies the required material characteristics. The above steps are repeated until the required material properties are satisfied.

(Construction of material database)
Next, a more specific method of constructing the material database DB will be described.
FIG. 3 is a flowchart showing the procedure for constructing and outputting the material database DB.
First, shape data of a layered product to be manufactured is input to the control section 45 shown in FIG. 1 (S11). The control unit 45 sets welding conditions according to the input shape data (S12). The welding conditions include parameters for changing the amount of heat input such as welding current. The shape data and welding condition information are sent from the control unit 45 to the stack planning unit 31, and the stack planning unit 31 creates a stack plan for the additively manufactured article (S13).

The control unit 45 drives the modeling unit 11 based on the created lamination plan (welding conditions) to form a weld bead for evaluation and produce a test piece (S14). The welded bead for evaluation formed at this time may be formed in accordance with the target shape of the laminate-molded object, but may simply be formed by forming only a portion of the laminate-molded object. In some cases, welding beads may simply be laminated on the same line on the surface of the base plate, regardless of the shape of the layered product.

FIG. 4 is an explanatory diagram schematically showing the correspondence between the material information measured from the formed weld bead and the temperature history profile obtained by simulation.
The test piece exemplified here has a structure in which weld beads B1 to B5 are stacked by repeatedly forming a weld bead B1 for evaluation on the base plate 23 and then forming a weld bead B2 directly above weld bead B1. .

First, the crystal grain size (for example, grain size) is measured by observing the cross section of a test piece in which the above-described weld beads B1 to B5 are laminated, and the hardness (for example, Vickers hardness) is also measured. In the example shown in FIG. 4, a plurality of sample points (for example, three points P1, P2, and P3) along the height direction (vertical direction) of weld bead B2 are examined according to the "Steel - Grain Size Microscope Test Method" ( Measure grain size based on JIS G 0551). Further, the Vickers hardness of the plurality of sample points is measured based on "Vickers hardness test - Test method" (JIS Z 2244) (S15). Note that each of the measurement methods described above is an example, and is not limited thereto.

On the other hand, this test piece is modeled to simulate the process of forming weld beads B1 to B5 (S16). In other words, a simulation is performed in which a weld bead is formed in a pseudo manner by calculation, and a temperature history profile in which the temperature rises and falls repeatedly due to the formation of weld beads B1 to B5 is obtained at multiple sample points (for example, three points P1, P2, and P3). (S17).

In the case shown in FIG. 4, the measured particle size at point P1 is D1 and Vickers hardness is Hv1, the particle size at P2 point is D2 and Vickers hardness is Hv2, and the particle size at P3 point is D3 and Vickers hardness. is Hv3.

Moreover, the temperature history profile of point P1, Prf2, and Pref3 are schematically shown in FIG.

Here, it is preferable that the simulation by the material prediction unit 33 uses a method with a fast calculation speed. The heat transfer analysis may be performed using a three-dimensional heat conduction equation. The material prediction unit 33 calculates the temperature history of the weld bead model using, for example, the following basic equation (1).

The basic formula (1) is a formula for heat transfer analysis using the so-called explicit FEM (Finite Element Method). Each parameter of basic formula (1) is as follows.
H: Enthalpy C: Reciprocal of nodal volume K: Heat conduction matrix F: Heat flux Q: Volumetric heat generation

According to this, nonlinear phenomena such as latent heat release can be calculated with high accuracy by using enthalpy as an unknown quantity. Note that the amount of heat input during welding is input into the parameters of volumetric heat generation or heat flow rate.

In the basic equation (1), which is the three-dimensional heat conduction equation, the amount of heat input during shaping (welding) may be applied to the welding area in accordance with the welding speed. Furthermore, if the welding bead is short, the heat input for the entire bead may be applied.

FIG. 5 is a graph showing a specific example of a simulated temperature history profile.
This temperature history profile represents the temperature change corresponding to weld bead B1 shown in FIG. The temperature history profile has a plurality of peaks corresponding to the formation of weld beads B1, B2, B3, B4, and B5. Each peak has a lower temperature because the weld bead in the upper layer is farther away from the weld bead B1.

Assuming that the melting point Tw of the weld bead is 1534°C, which is the melting point of iron (carbon steel), and the transformation point Tt of the weld bead (A1 transformation point of carbon steel) is 723°C, the material of the weld bead after solidification is It is generally determined by the temperature history in the range from the point Tt to the melting point Tw. That is, in additive manufacturing, heat input and cooling are repeated, but the factor that affects the structure of the additively manufactured product is the temperature history within the above range. Therefore, the feature amount of the temperature history in the range from the transformation point Tt to the melting point Tw (hereinafter referred to as the test temperature range Aw) is extracted.

As shown in FIG. 5, the temperature history profile has multiple peaks, but the peaks above the melting point Tw and the peaks below the transformation point Tt are ignored. Among the peaks in the test temperature range Aw above the transformation point Tt and below the melting point Tw, the temperature of the low-temperature side maximum point Pk2 closest to the transformation point Tt, and the temperature of the high-temperature side maximum point Pk1 second closest to the transformation point Tt. Extract. The temperatures of these maximum point Pk1 on the high temperature side and maximum point Pk2 on the low temperature side are set as the feature quantity of the temperature history.

The crystal grain size (grain size) and hardness (Vickers hardness) of the structure obtained in this way, and the temperature information of the high temperature side maximum point Pk1 and the low temperature side maximum point Pk2 are correlated with each other and registered in the material database ( S18).

FIG. 6 is an explanatory diagram showing a specific example of data elements to be registered in the material database DB.
It is preferable that the material database DB is configured to include map data MDA, MDB, MDC, .

Here, map data MDA with a heat input amount of QA will be explained as an example. The map data MDA includes the above-mentioned information on crystal grain size and hardness according to the temperature of the high-temperature side maximum point Pk1 that appears in the first pass and the temperature of the low-temperature side maximum point Pk2 that appears in the second pass within the inspection temperature range Aw. is mapped into a two-dimensional matrix.

Now, it is assumed that the maximum point Pk1 on the high temperature side and the maximum point Pk2 on the low temperature side at the sample points P1, P2, and P3 of the weld bead B2 shown in FIG. 4 have the following values.
P1 Pk1: 1150℃, Pk2: 810℃
P2 Pk1: 1270℃, Pk2: 950℃
P3 Pk1: 1020℃, Pk2: 760℃

In that case, in the map data MDA, data elements (information on crystal grain size and hardness) of sample points P1, P2, and P3 are registered in the matrix corresponding to the high temperature side maximum point Pk1 and the low temperature side maximum point Pk2, respectively. Although three sample points are illustrated, temperature history profiles at any number of sample points can be easily created by simulation. Therefore, temperature history profiles of a large number of sample points are determined by simulation, and data elements Pk1 and Pk2 are automatically extracted from each temperature history profile.

On the other hand, data elements such as the grain size and hardness of the structure at a large number of sample points may be measured one by one, but depending on the degree of material change at each measurement position, the data elements for sample points included in a specific area may be measured one by one. The measured grain size and hardness at one point can also be used in common for each sample point.

According to this, data elements can be easily registered in each matrix of the map data MDA shown in FIG. 6. In other words, compared to the case where the information of each matrix is measured and registered one by one, the construction of map data can be made much faster.

The above is a procedure for constructing the map data MDA in the case of the heat input amount QA, but the same construction can be performed for the map data in the case where the heat input amount is changed (S19). That is, a test piece is prepared based on a lamination plan created by changing the amount of heat input, and the crystal grain size and hardness are measured in the same manner as described above. Further, by simulating the formation of weld beads based on the lamination plan, a temperature history profile is obtained in the same manner as described above, and the maximum point Pk1 on the high temperature side and the maximum point Pk2 on the low temperature side are determined. By registering the data elements obtained in this manner in each matrix, map data MDB, MDC, . . . can be constructed with high efficiency.

In this way, the material database DB, which is composed of a plurality of constructed map data MDA, MDB, MDC, ... By registering it in the database in association with the maximum point Pk1 and the maximum point Pk2 on the low temperature side, it can be constructed efficiently and in a short time. The created material database DB is output to the storage unit 39 in FIG. 1 and stored in the storage unit 39 (S20).

Here, the temperature history (Figure 2) of the additively manufactured object includes many maximum points due to repeated heat input and cooling, but the maximum points that affect the material quality are within the test temperature range above the transformation point and below the melting point. 1 to 2 points that fall within the range. By extracting such local maximum points as representative information, the amount of information stored can be reduced. In other words, compared to the case where the entire temperature history profile is registered in a database, the amount of information to be registered can be significantly reduced. Although the explanation here assumes that the number of maximum points extracted is two, it may be one or three or more depending on the conditions. As shown in FIG. 6, by mapping information on crystal grain size and hardness in a matrix according to the temperature range of two maximum points, it is possible to finely classify the material of the weld bead.

The material of the molten bead changes depending on the cooling rate after the bead is formed. When the cooling rate is slow, the grain size becomes large, and when the cooling rate is fast, it becomes dense. In particular, the farther the low temperature side maximum point Pk2 is from the transformation point Tt, the more likely the acicular structure remains. It can be assumed that such a cooling rate depends on the amount of heat input.

Figure 7 is a graph showing the difference in cooling characteristics when beads are formed with different amounts of heat input. It is a graph showing temperature change characteristics in the case of heat amount.

As shown in Figure 7 (A), even if the heat input is increased in the order of Test Example 1, Test Example 2, Test Example 3, and Test Example 4, the time required to cool down to about 350°C remains almost unchanged. , in the case of (A) in FIG. 7, it is approximately 15 seconds (see Pend). On the other hand, as shown in FIG. 7B, when the amount of heat input is relatively low, if the cooling time is about 15 seconds, the temperature will be reduced to about 300° C. (see Pend). That is, the higher the heat input, the slower the cooling rate, and the lower the heat input, the faster the cooling rate. Therefore, the cooling rate depends on the amount of heat input, and if the temperature of the low temperature side maximum point Pk2 is known, the structure of the weld bead can be predicted. By predicting the structure by combining the temperature of the low-temperature side maximum point Pk2 and the temperature of the high-temperature side maximum point Pk1, the prediction accuracy is improved compared to the case of predicting only using either temperature.

Furthermore, when the material of the weld bead is sorted using the cooling rate as a parameter, it is necessary to consider the contribution of each modeling condition to the cooling rate when modifying the lamination plan, making calculations extremely complicated. In this respect, if the amount of heat input is used as a parameter as described above, it can be easily calculated from conditions such as welding current and welding speed. Therefore, by generating map data for each amount of heat input, it becomes easier to modify the stacking plan based on the prediction results. Furthermore, by constructing a material database for each composition of the layered product and the type of filler metal, it becomes possible to fine-tune the layering plan.

(Lamination planning method for first additively manufactured product)
Next, using the material database constructed and prepared in advance as described above, predict the material of the layered object to be manufactured, change the welding conditions to satisfy the required material characteristics, and plan the layered structure. This section explains the steps to create a modeling program based on this layered plan.

FIG. 8 is a flowchart showing the steps of the first layer planning method that satisfies the required material properties.
First, shape data of a layered product to be manufactured is input to the control unit 45 shown in FIG. 1 (S21). The control unit 45 sets various conditions such as welding conditions according to the input shape data (S22). The welding conditions include parameters for changing the amount of heat input such as welding current. The shape data and welding condition information are sent from the control unit 45 to the stack planning unit 31, and the stack planning unit 31 creates a stack plan for the additively manufactured article (S23).

Then, the control unit 45 predicts, by simulation, the material (crystal grain size, hardness) of the layered product when it is modeled based on the created layered plan (S24). That is, a temperature history profile in each part of the laminate-molded object is determined, and a high temperature side maximum point Pk1 and a low temperature side maximum point Pk2 are determined from the temperature history profile. The materials (crystal grain size, hardness) of the weld bead corresponding to these maximum points Pk1 on the high temperature side and maximum points Pk2 on the low temperature side are determined by referring to the material database DB. At this time, if the same data does not exist in the material database DB, it may be determined by interpolation or extrapolation using data close to it.

Next, the determination unit 35 determines whether the predicted material of the weld bead satisfies desired material properties. If the required material characteristics are not satisfied, the control unit 45 changes the heat input amount during welding, for example by adjusting the welding current (S26), and creates the lamination plan again (S23). This process is repeated until the required material properties are satisfied. When an appropriate amount of heat input that satisfies the required material properties is obtained, the modeling program creation unit 37 creates a modeling program that causes the modeling unit 11 to execute a lamination plan according to the amount of heat input (S27). The created modeling program is stored in the storage unit 39 and read into the control unit 45 when manufacturing a layered object.

According to this procedure, the amount of heat input that satisfies the required material characteristics of the additively manufactured object is always selected, and additive manufacturing can be performed with an appropriate layering plan. In particular, even a user with little specialized knowledge regarding setting welding conditions can easily optimize the stacking plan.

(Second layer planning method for layered product)
In addition, using a pre-prepared tissue database, predict the material of the additively manufactured object, select a filler material that satisfies the required characteristics of the material, create a lamination plan, and create a manufacturing program based on this lamination plan. You may.
In that case, the same process can be performed except that the step of changing the amount of heat input (S26) in the flowchart shown in FIG. 8 is replaced with the step of changing the type of filler metal.

That is, the determination unit 35 determines whether the predicted material of the weld bead satisfies desired material properties. If the required material properties are not satisfied, the control unit 45 changes the filler metal used for welding to another type of filler metal and creates a lamination plan again (S23). This process is repeated until the required material properties are satisfied.

With this procedure as well, the amount of heat input that satisfies the required material characteristics of the additively manufactured object is always selected, and additive manufacturing can be performed with an appropriate layering plan. In particular, even a user with little specialized knowledge regarding filler metals can easily optimize the lamination plan.

(Third layer planning method for layered product)
FIG. 9 is a flowchart showing the steps of a third layer planning method that satisfies required material properties.
First, various requirements such as the shape data of the layered product to be manufactured, the type of filler metal, and the required material properties of the welding bead are input to the control unit 45 shown in FIG. 1 (S31). The control unit 45 searches the material database for data elements that match the input requirements. For example, information on combinations of local maximum points with a specific grain size and hardness is obtained. Then, the stack planning unit 31 creates a stack plan based on the matched data element conditions (S33).

The material prediction unit 33 predicts the material of the weld bead when the weld bead is formed according to the created lamination plan. The determination unit 35 compares the predicted result with the required material properties (S34), and if the predicted result does not satisfy the required material properties, changes the type of filler metal and sends the request to the stack planning unit 31 again. , to create a stacking plan (S33).

When the lamination plan that satisfies the required material properties is created, the modeling program creating section 37 creates a modeling program that drives the modeling section 11 based on the lamination plan (S36).

According to this procedure, even if the required material characteristics of the additively manufactured product cannot be satisfied by adjusting the amount of heat input described above, additive manufacturing can be performed with an appropriate layering plan by changing the filler metal. Therefore, the range of adjustment of the stacking plan is expanded, and the degree of freedom in design is improved.

In addition, the target material that satisfies the required material characteristics of the weld bead (crystal grain size, hardness, etc.) and the constraints on the bead shape when forming the weld bead (shape and size of the additively manufactured object, etc.) is searched in the material database. If the material information corresponding to the target material is detected by searching from the material information possessed by the target material, the type of filler metal corresponding to that material information may be determined as the recommended filler material to be used. . According to this method, the recommended filler material to be used for modeling can be optimally determined by predicting the material quality.

Furthermore, when pseudo-reproducing the process of additive manufacturing using a computer simulation based on the above-mentioned lamination plan, it is necessary to consider the manufacturing conditions of the additively-produced product, such as the inter-pass time and heat input in the path (travel path) of the divided welding bead. It is also possible to extract an arbitrary set amount such as. Thereby, various conditions for additive manufacturing can be easily specified without requiring specialized knowledge.

The above-mentioned transformation point of the welded bead is exemplified by the A1 transformation point, which is the critical temperature at which carbon steel can be hardened, but is not limited thereto. For example, the A2 transformation point (770°C) is the critical temperature at which a strong magnetism occurs, the A3 transformation point (910°C) results in a gamma (γ) iron structure, and the A4 transformation point (1400°C), which results in a delta (δ) iron structure. Various transformation points can be applied, such as (°C). Even for materials other than carbon steel, the transformation point that determines the structure may be selected in the same manner.

The present invention is not limited to the embodiments described above, and those skilled in the art may combine the configurations of the embodiments with each other, or make changes and applications based on the description of the specification and well-known techniques. This is the intended purpose of the invention and falls within the scope for which protection is sought.

As mentioned above, the following matters are disclosed in this specification.
(1) A method for predicting the material quality of an additively manufactured product in which welded beads made by melting and solidifying a filler material are laminated, the method comprising:
acquiring a temperature history profile representing a temperature change of a specific weld bead during formation of the weld bead of the laminate-molded object;
extracting a plurality of local maximum points in the temperature history profile that are included in a test temperature range that is below the melting point of the weld bead and above the transformation point of the weld bead;
The material information corresponding to the extracted temperature combination of the maximum points is extracted by referring to a material database in which material information of the welding bead corresponding to the temperature of the maximum point is associated in advance, and the material information is applied to the welding bead. A process of outputting as a bead material prediction result,
A method for predicting material properties of additively manufactured objects.
According to this method for predicting the material properties of additively manufactured objects, a combination of temperatures at the maximum points of the temperature history of the weld bead is made by referring to a material database that associates multiple maximum points of the temperature history profile with material information of the weld bead. By obtaining material information corresponding to , it is possible to easily predict the material of the layered object to be manufactured.

(2) The method for predicting material quality of a layered product according to (1), wherein the maximum points extracted from the temperature history profile are two points selected in order of proximity to the transformation point within the inspection temperature range.
According to this method for predicting the material quality of a laminate-molded object, by extracting two local maximum points as representative information, it is possible to reduce the amount of information stored.

(3) The material information included in the material database includes, within the inspection temperature range, the temperature of a low-temperature maximum point closest to the transformation point, and the temperature of a high-temperature maximum point second closest to the transformation point. The method for predicting the material quality of a layered product according to (2), which includes map data on which tissue information of the welded bead is mapped.
According to this method for predicting the material quality of additively manufactured objects, the temperature of the maximum point on the high temperature side, which is close to the transformation point that most affects the material quality of the weld bead, and the temperature of the maximum point on the low temperature side are mapped in a matrix, so that welding Bead materials can be classified in detail. Therefore, the accuracy of predicting material quality can be improved.

(4) The method for predicting the material quality of an additively manufactured article according to (3), wherein the material information includes information on the crystal grain size and hardness of the welded bead.
According to this method for predicting the material quality of a laminate-produced object, accurate and appropriate strength evaluation can be performed by using crystal grain size and hardness, which are highly correlated with mechanical strength, as structure information.

(5) The source map data is classified according to the amount of heat input applied to the formation of the weld bead, and the map data to be referred to is switched according to the amount of heat input. Method.
According to this method for predicting the material quality of a laminate-molded object, the material quality can be predicted more accurately by using map data according to the amount of heat input.

(6) The temperature history profile is generated by computer simulation of the temperature history when melting and solidifying the filler metal to form the weld bead. A method for predicting the material properties of an additively manufactured object described in .
According to this method for predicting the material quality of a laminate-molded object, by obtaining a temperature history profile through simulation, profiles with different conditions can be generated easily and in a shorter time than when actually measuring.

(7) A method for constructing a material database having data elements representing the relationship between material information of a laminate-produced product in which welded beads made by melting and solidifying filler metal and the temperature history of the welded beads, the method comprising:
generating a temperature history profile representing a temperature change of a specific weld bead during formation of the weld bead of the laminate-molded object by computer simulation;
extracting a plurality of local maximum points in the temperature history profile that are included in a test temperature range that is below the melting point of the weld bead and above the transformation point of the weld bead;
storing the data element that associates the material information of the weld bead formed by the temperature history profile with the combination of temperatures of the plurality of local maximum points;
How to build a material database including:
According to this material database construction method, the temperature history profile is determined by computer simulation, so that a large number of types of profiles can be generated easily and in a short time, and the material database can be constructed with high efficiency.

(8) The material database construction method according to (7), wherein the material information includes information on the crystal grain size and hardness measured from the weld bead.
According to this material database construction method, a material database that allows accurate and appropriate strength evaluation can be constructed by using crystal grain size and hardness, which are highly correlated with mechanical strength, as structure information.

(9) The method of constructing a material database according to (7) or (8), wherein a plurality of sets of the data elements are generated and stored from the temperature history profiles at a plurality of mutually different positions of the layered product.
According to this material database construction method, the amount of information stored can be reduced and the amount of information registered in the database can be significantly reduced.

(10) The method for constructing a material database according to (7) or (8), wherein the data element is generated and stored for each amount of heat input applied to forming the weld bead.
According to this material database construction method, by storing data elements for each amount of heat input, it is possible to construct a material database that allows more accurate prediction.

(11) A layer planning method for a layered product in which welded beads made by melting and solidifying a filler material are layered, the method comprising:
A first step of predicting the material of the welded bead constituting the laminate-molded article by the method for predicting the material of the laminate-molded article according to any one of (1) to (6);
If the prediction result of the material in the first step does not satisfy the preset required material characteristics of the weld bead, the amount of heat input applied to the formation of the weld bead is changed, and the weld bead is formed with the changed amount of heat input. a second step of predicting the material of the welding bead again using the material prediction method of the laminate-molded object;
has
A laminate planning method for a laminate-molded article, wherein the second step is repeated until the prediction result of the material in the second step satisfies the required material characteristics.
According to this layer planning method for a layered product, by changing the amount of heat input, a welded bead having desired material properties can be obtained.

(12) A layer planning method for a layered product in which welded beads made by melting and solidifying a filler material are layered, the method comprising:
A first step of predicting the material of the welded bead constituting the laminate-molded article by the method for predicting the material of the laminate-molded article according to any one of (1) to (6);
If the prediction result of the material in the first step does not satisfy the preset required material characteristics of the weld bead, the type of the filler metal is changed, and the weld bead is formed with the changed filler metal. a second step of predicting the material of the layer again using the material prediction method of the laminate-molded object;
has
A laminate planning method for a laminate-molded article, wherein the second step is repeated until the prediction result of the material in the second step satisfies the required material characteristics.
According to this layer planning method for a layered product, by changing the filler material, a welded bead having desired material properties can be obtained.

(13) A layer planning method for a layered product in which welded beads made by melting and solidifying a filler material are layered, the method comprising:
a filler material selection step of determining a recommended filler material to be used in the layered product by referring to a material database including material information of the welding bead;
The material database includes an inspection of a temperature history profile representing a temperature change of a specific weld bead at a temperature below the melting point of the weld bead and above the transformation point of the weld bead during formation of the weld bead of the laminate-molded object. Having material information of the weld bead corresponding to a combination of temperatures of a plurality of local maximum points included in the temperature range for each type of the filler metal,
In the filler metal selection process,
Searching from the material information in the material database for a target material that satisfies the required material characteristics of the weld bead and constraints on the bead shape when forming the weld bead,
If the material information corresponding to the target material can be detected, determining the type of filler metal corresponding to the material information as the recommended filler material to be used;
Laminate planning method for additively manufactured objects.
According to this layer planning method for a layered product, it is possible to predict and determine the type of filler material that can obtain the desired material properties and form a weld bead that satisfies the constraint conditions.

(14) A temperature history profile of the weld bead is determined by computer simulation according to the maximum point of the temperature history profile corresponding to the detected material information, and manufacturing conditions of the layered product corresponding to the temperature history profile are determined. The laminate planning method for a laminate-molded article according to (13), further comprising the step of specifying.
According to this layer planning method for a layered product, manufacturing conditions for the layered product can be specified by simulation according to the maximum point of the temperature history profile.

(15) The layer planning method for a laminate-molded article according to (14), wherein the manufacturing conditions for the laminate-molded article include at least one of an interpass time and an amount of heat input when forming the welded bead.
According to this layer planning method for a layered product, manufacturing conditions such as inter-pass time and heat input are determined, and welding conditions can be easily set.

(16) A method for manufacturing a laminate-produced article, comprising manufacturing the laminate-produced article in accordance with a procedure planned by the laminate-planning method for a laminate-produced article according to any one of (11) to (15).
According to this method for producing a laminate-molded article, the material of the weld bead can be produced with desired characteristics.

11 Modeling section 13 Controller 15 Power supply 17 Torch 19 Welding robot 21 Filler material supply section 23 Base plate 31 Lamination planning section 33 Material prediction section 35 Judgment section 37 Modeling program creation section 39 Storage section 41 Input section 43 Output section 45 Control section 51 Data element 100 Additive manufacturing equipment

Claims (16)

A method for predicting the material quality of an additively manufactured article in which welded beads made by melting and solidifying a filler material are laminated, the method comprising:
acquiring a temperature history profile representing a temperature change of a specific weld bead during formation of the weld bead of the laminate-molded object;
extracting a plurality of local maximum points in the temperature history profile that are included in a test temperature range that is below the melting point of the weld bead and above the transformation point of the weld bead;
The material information corresponding to the extracted temperature combination of the maximum points is extracted by referring to a material database in which material information of the welding bead corresponding to the temperature of the maximum point is associated in advance, and the material information is applied to the welding bead. A process of outputting as a bead material prediction result,
A method for predicting material properties of additively manufactured objects. 2. The method for predicting material quality of a layered product according to claim 1, wherein the maximum points extracted from the temperature history profile are two points selected in order of proximity to the transformation point within the inspection temperature range. The material information included in the material database corresponds to the temperature of a low-temperature maximum point closest to the transformation point and the temperature of a high-temperature maximum point second closest to the transformation point within the inspection temperature range. 3. The method for predicting material properties of a layered product according to claim 2, further comprising map data on which the structure information of the welded bead is mapped. 4. The method for predicting the material quality of a layered product according to claim 3, wherein the material information includes information on the crystal grain size and hardness of the welded bead. 4. The method for predicting the material quality of a laminate-molded object according to claim 3, wherein the map data is classified according to the amount of heat input applied to the formation of the weld bead, and the map data to be referred to is switched depending on the amount of heat input. The laminate according to any one of claims 1 to 5, wherein the temperature history profile is generated by computer simulation of the temperature history when the filler metal is melted and solidified to form the weld bead. A method for predicting the material properties of objects. A method for constructing a material database having data elements representing a relationship between material information of a layered product in which welded beads made by melting and solidifying a filler material and a temperature history of the welded beads, the method comprising:
generating a temperature history profile representing a temperature change of a specific weld bead during formation of the weld bead of the laminate-molded object by computer simulation;
extracting a plurality of local maximum points in the temperature history profile that are included in a test temperature range that is below the melting point of the weld bead and above the transformation point of the weld bead;
storing the data element that associates the material information of the weld bead formed by the temperature history profile with the combination of temperatures of the plurality of local maximum points;
How to build a material database including: 8. The method of constructing a material database according to claim 7, wherein the material information includes information on crystal grain size and hardness measured from the weld bead. The method of constructing a material database according to claim 7 or 8, wherein a plurality of sets of the data elements are generated and stored from the temperature history profiles at a plurality of mutually different positions of the layered product. The method for constructing a material database according to claim 7 or 8, wherein the data element is generated and stored for each amount of heat input applied to forming the weld bead. A layer planning method for a layered product in which welded beads made by melting and solidifying a filler material are layered, the method comprising:
A first step of predicting the material of the weld bead constituting the laminate-molded article by the method for predicting the material quality of the laminate-molded article according to any one of claims 1 to 6;
If the prediction result of the material in the first step does not satisfy the preset required material characteristics of the weld bead, the amount of heat input applied to the formation of the weld bead is changed, and the weld bead is formed with the changed amount of heat input. a second step of predicting the material of the welding bead again using the material prediction method of the laminate-molded object;
has
A laminate planning method for a laminate-molded article, wherein the second step is repeated until the prediction result of the material in the second step satisfies the required material characteristics. A layer planning method for a layered product in which welded beads made by melting and solidifying a filler material are layered, the method comprising:
A first step of predicting the material of the weld bead constituting the laminate-molded article by the method for predicting the material quality of the laminate-molded article according to any one of claims 1 to 6;
If the prediction result of the material in the first step does not satisfy the preset required material characteristics of the weld bead, the type of the filler metal is changed, and the weld bead is formed with the changed filler metal. a second step of predicting the material of the layer again using the material prediction method of the laminate-molded object;
has
A laminate planning method for a laminate-molded article, wherein the second step is repeated until the prediction result of the material in the second step satisfies the required material characteristics. A layer planning method for a layered product in which welded beads made by melting and solidifying a filler material are layered, the method comprising:
a filler material selection step of determining a recommended filler material to be used in the layered product by referring to a material database including material information of the welding bead;
The material database includes an inspection of a temperature history profile representing a temperature change of a specific weld bead at a temperature below the melting point of the weld bead and above the transformation point of the weld bead during formation of the weld bead of the laminate-molded object. Having material information of the weld bead corresponding to a combination of temperatures of a plurality of local maximum points included in the temperature range for each type of the filler metal,
In the filler metal selection process,
Searching from the material information in the material database for a target material that satisfies the required material characteristics of the weld bead and constraints on the bead shape when forming the weld bead,
If the material information corresponding to the target material can be detected, determining the type of filler metal corresponding to the material information as the recommended filler material to be used;
Laminate planning method for additively manufactured objects. A step of determining the temperature history profile of the welding bead through computer simulation according to the maximum point of the temperature history profile corresponding to the detected material information, and specifying the manufacturing conditions of the layered product corresponding to the temperature history profile. The laminate planning method for a laminate-molded article according to claim 13, further comprising: 15. The layer planning method for a laminate-molded article according to claim 14, wherein the manufacturing conditions for the laminate-molded article include at least one of an interpass time and an amount of heat input when forming the welded bead. A method for manufacturing a laminate-molded article, comprising manufacturing the laminate-molded article in accordance with a layer-planning procedure according to the layer-planning method for a laminate-molded article according to any one of claims 11 to 15.

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