WO2017199551A1

WO2017199551A1 - Additive manufacturing data generating device, additive manufacturing system, and product

Info

Publication number: WO2017199551A1
Application number: PCT/JP2017/009534
Authority: WO
Inventors: 佐竹　弘之; 青田　欣也; 孝介桑原
Original assignee: 株式会社日立製作所
Priority date: 2016-05-16
Filing date: 2017-03-09
Publication date: 2017-11-23

Abstract

To reduce processing costs associated with weight reduction, provided is an additive manufacturing data generating device, comprising: a porous body database (111) in which information is stored wherein a relative density in a structure which is to be manufactured by performing additive manufacturing is associated with a degree of gaps in a porous body; a structure analysis processing unit (102) which computes a stress distribution which relates to physical properties in the structure; and a porous body positioning unit (104) which, on the basis of the computed stress distribution, computes a feature value distribution which is a distribution of feature values in the structure, determines the porous body which corresponds to a computed relative density, and replaces data of the structure with data of the determined porous body.

Description

Layered modeling data generation device, layered modeling system and product

The present invention relates to an additive manufacturing data generation apparatus, additive manufacturing system, and product technology for generating a structure by additive manufacturing.

In the additive manufacturing method used in a 3D (Dimension) printer or the like, the following steps are performed. That is, a melted and solidified layer is generated by irradiating the powder layer with a laser beam or an electron beam. And the powder layer is newly coat | covered with respect to the produced | generated melt | dissolved solidification layer, A laser beam etc. are irradiated to this powder layer. As a result, a new melt-solidified layer is laminated on the lower melt-solidified layer. By repeating such a process, an integrated melt-solidified body, that is, a modeled object is modeled. According to the additive manufacturing method, a final part that is directly integrated can be obtained without the need for machining or assembling. Therefore, the part can be easily manufactured using a difficult-to-work material. In addition, the component manufacturing by additive manufacturing can easily realize a complicated shape, so that the hollow structure can reduce the weight.

On the other hand, a design technique based on topology optimization is used for weight reduction by the hollow structure. In topology optimization, a weight-reduced shape is derived by minimizing the mass of a structure to which an external force is applied while suppressing stress and deformation below an allowable value. There are many commercially available general-purpose software that performs topology optimization, and many of these software adopt a lightening algorithm called a density method. In the density method, the Young's modulus indicating the rigidity of the material is expressed by density. In the density method, the density value is calculated so that the deformation is reduced when an external force is applied to a virtual material having an intermediate density. Here, the intermediate density ρ is calculated by rd · ρ ₀ (0 ≦ rd ≦ 1, ρ ₀ is the original density of the material of the substance, and rd is the relative density). In the weight reduction method using the density method, it is necessary to repeatedly calculate until the value of the relative density becomes 0 or 1, and to indicate a region where the thickness can be removed without contributing to rigidity with respect to the action of the external force. That is, in the structure manufactured by the density method, there is no intermediate density, and only a region where the relative density is 0 (void) or 1 (non-void) is present.

As a conventional technique related to weight reduction by topology optimization, for example, there is a technique disclosed in Patent Document 1. Patent Document 1 describes “a structure analysis method for performing a structure analysis using topology optimization based on a density method for a structure (2) to which an external force F is applied, and in particular, an external force F is applied to the structure. The step of identifying the load region (6) and the thickness set to such an extent that the strength of the structure (2) is not affected along at least the load region (6) of the structure (2). A structural analysis method characterized in that it comprises a step of providing a shell member (8) (see abstract).

JP 2015-111132 A

However, in the method of providing the shell member described in Patent Document 1, a light weight shape by topology optimization is required by repeatedly calculating until the value of the relative density becomes 0 or 1. For this reason, the technique described in Patent Document 1 requires calculation time, and there is a problem in design cost. Moreover, the weight reduction shape derived | led-out by the technique of patent document 1 is dependent on the mesh data used for the structural analysis. That is, in the structural analysis, the three-dimensional shape data is divided by a mesh larger than the element in the three-dimensional shape data. And in the technique of patent document 1, 3D printer apparatus models based on the mesh in a structural analysis. Therefore, the structure manufactured based on the weight-reduced shape derived from Patent Document 1 has unevenness and a constriction in the thinned region, and requires manual correction.

The present invention has been made in view of such a background, and an object of the present invention is to reduce the cost of processing in weight reduction.

In order to solve the above-described problem, the present invention relates to a feature amount-porous body information in which a feature amount in a structure to be modeled by additive manufacturing is associated with a degree of the void in a porous body having a void. Is stored in the storage unit, the physical property information estimation unit for estimating the physical property information in the structure, and the feature amount distribution that is the distribution of the feature amount in the structure based on the estimated information on the physical property. Based on the feature quantity distribution calculation unit to be calculated and the feature quantity-porous body information, the porosity of the porous body corresponding to the calculated distribution of the feature quantity is determined, and the determined porous body data is used to determine the porosity of the porous body. And a porous body arrangement part that replaces data of the structure.
Other solutions will be described in the embodiments.

According to the present invention, the processing cost for weight reduction can be reduced.

It is a functional block diagram of additive manufacturing system Z concerning this embodiment. It is a figure which shows the outline example of the porous body in a 1st method. It is a figure which shows the determination method of the diameter of a porous body. It is a figure which shows the example of a graph of the function which shows the diameter of a porous body. It is a figure which shows the example of the correspondence of the relative density in a 2nd method, and a porous body. It is a flowchart which shows the procedure of the layered modeling data generation process which concerns on this embodiment. It is a figure which shows the example of the setting screen which concerns on this embodiment. It is a figure which shows the example of the structure used as a process target. It is a figure which shows the stress distribution as a result of having performed the structure analysis process and the stress distribution calculation process. It is a figure which shows the relative density distribution in a structure. It is a figure which shows the shape of a weight reduction golf club head. It is a figure which shows the example of the weight reduction golf club head laminated-modeled based on the weight reduction shape data produced | generated by 3D printer apparatus. It is a conceptual diagram of a general 3D printer apparatus. It is a graph which shows the calculation cost at the time of reducing the weight of a golf club head by the conventional method. It is a figure which shows the relative density distribution of the golf club head obtained by the method until now. It is a figure which shows the shape of the weight reduction golf club head produced by the method until now. It is a figure which shows the result of having performed the smoothing process with respect to the weight-reduced golf club head shape created by the method until now.

Next, modes for carrying out the present invention (referred to as “embodiments”) will be described in detail with reference to the drawings as appropriate.

[system]
FIG. 1 is a functional block diagram of the additive manufacturing system Z according to the present embodiment.
In FIG. 1, the layered modeling system Z has a configuration in which a layered modeling data generation device 1, a D printer device (modeling unit) 2, and an input device 3 are connected to each other.
The input device 3 is for a user to input data necessary for calculating a weight-reduced shape of a structure (object to be layered). The input device 3 is, for example, a tablet PC (Personal Computer), a PC, a workstation, a computer server, or the like. Information stored in a terminal input device such as a keyboard provided in these devices, the Internet, or an external storage device is transmitted to the additive manufacturing data generation device 1.
In the present embodiment, the layered modeling data generation device 1 and the input device 3 are separate devices, but may be an integrated device.

The layered modeling data generation device 1 includes a memory 100, a CPU 120, a transmission / reception device 121, and the like. The memory 100 is loaded with a program stored in a storage device (not shown). Then, the loaded program is executed by the CPU 120. Thus, the processing unit 101, the structural analysis processing unit (physical property information estimation unit, feature amount calculation unit) 102, the weight reduction processing unit 103, and the porous body arrangement processing unit 104 constituting the processing unit 101 are embodied.
The transmission / reception device 121 receives information from the input device 3 and transmits information to the 3D printer device 2.

When the layered modeling data generation apparatus 1 acquires data necessary for the layered modeling data generation process from the input device 3, the layered modeling data generation apparatus 1 generates weight-reduced shape data by performing a layered modeling data generation process described later. Then, the generated weight reduction shape data is transmitted to the 3D printer apparatus 2.
The structural analysis processing unit 102 performs a structural analysis calculation using the three-dimensional shape data, and calculates a stress distribution based on the structural analysis calculation result.
The weight reduction processing unit 103 calculates a relative density distribution based on the extracted stress distribution. The relative density is a density relative to the original density of the substance. Further, the weight reduction processing unit 103 calculates the total mass and the like based on the calculated distribution of relative density and the like, and determines whether or not the weight reduction condition (described later) is satisfied.
The porous body arrangement processing unit 104 generates weight-reduced shape data in which porous body data that is porous body data is arranged in the three-dimensional shape data in accordance with the calculated relative density. The porous material will be described later.
Detailed processing performed by each of the units 101 to 104 will be described later.

The additive manufacturing data generation apparatus 1 includes a porous body DB (storage unit) 111, a shape DB 112, a stress distribution DB 113, a density distribution DB 114, and a weight-reduced shape DB 115.
The porous body DB 111 stores information related to porous body data that is pasted according to the relative density of the structure.
The shape DB 112 stores three-dimensional shape data. The three-dimensional shape data is STL (Standard Triangulated Language) data generated by dedicated software or the like. The STL data is composed of a plurality of node data. In the STL data, a three-dimensional shape is represented by a triangular element composed of such three nodes and a normal vector indicating the direction of the surface of the triangular element. This triangular element is obtained by dividing the surface of the structure into finite elements. Stress values and relative density values calculated later are calculated corresponding to the triangular elements and stored in the stress distribution DB 113 and the density distribution DB 114. Hereinafter, the triangular element in the STL data is simply referred to as an element. In addition, the arrangement of the porous body data and the porous body of the three-dimensional shape data is also performed in element units. Incidentally, the STL data is standard three-dimensional shape data used when layered modeling is performed using the 3D printer apparatus 2.

In the stress distribution DB 113, data related to the stress distribution calculated by the structural analysis processing unit 102 is stored.
The density distribution DB 114 stores data related to the relative density distribution calculated by the weight reduction processing unit 103.
The weight reduction shape DB 115 stores weight reduction shape data. The weight reduction shape data is three-dimensional shape data in which weight reduction is realized by the porous body arrangement processing unit 104 arranging the porous body data corresponding to the relative density in the three-dimensional shape data. In the present embodiment, the three-dimensional shape data input to the layered modeling data generation device 1 is described as “three-dimensional shape data”. The three-dimensional shape data generated by the additive manufacturing data generation device 1 is described as “weight reduction shape data”.

This embodiment is characterized in that, in the layered modeling data generation process, the porous body arrangement processing unit 104 generates the weight reduction shape data by arranging the porous body data according to the relative density distribution.

The 3D printer apparatus 2 manufactures a structure that is lightened by additive manufacturing based on the weight-reduced shape data of the structure generated by the additive manufacturing data generation apparatus 1.

[Porous material]
Next, the porous body according to the present embodiment will be described with reference to FIGS. 2A to 3.
(First method)
FIG. 2A is a diagram showing a schematic example of a porous body in the first method, FIG. 2B is a diagram showing a method of determining the diameter of the porous body, and FIG. 2C is a graph example of a function showing the diameter of the porous body FIG.
The first method shown in FIGS. 2A to 2C is a method for determining the diameter of the hole 202 in the porous body 201 according to the relative density of the structure by using a function.
The first method is executed by a built-in processing routine for generating a porous body shape. The built-in processing routine for porous body shape generation is started when the user checks the default setting check field 361 in the relative density-porous body data setting unit 360 described later in FIG.

In this processing routine, the relative density rd (0 ≦ rd ≦ 1) in the structure is given as an argument, and when called, the shape of the porous body 201 having the porosity (1-rd) shown in FIG. This routine returns with data.
As shown in FIG. 2A, the hole 202 in the porous body 201 is formed in a uniform cylindrical shape having a diameter d facing one direction. That is, the hole 202 is a uniform circle having a diameter d. As shown in FIG. 2A, when the distances between the holes 202 are X in the x-axis direction and Y in the y-axis direction, the holes 202 are arranged in a grid pattern at equal intervals so that the center distance of the holes 202 becomes X = Y. The
Here, if X = Y = 1, the relationship between the relative density rd and the diameter d of the hole 202 is shown by the relational expression shown in FIG. 2B. According to this relational expression, if the relative density rd is given, the size of the hole 202 in the porous body 201 can be uniquely determined.

2C, the horizontal axis represents the relative density rd of the structure, the vertical axis represents the diameter d of the hole 202, and the relationship between the relative density rd and the diameter d of the hole 202 shown in FIG. .
According to the graph 211, if the relative density rd of the argument is designated, the diameter d of the hole 202 in the porous body 201 is uniquely determined. However, as indicated by the graph 211 in FIG. 2C, the value of the diameter d is 1 at the point 212 having a relative density of 0.785, which is the same as the interval at which the holes 202 are arranged. That is, the holes 202 are connected to each other. Therefore, if the diameter d is further increased, the holes 202 overlap (holes 202 are connected), and the porous body 201 having the specified relative density cannot be obtained. Therefore, the first method can be applied in the range where the relative density rd is 0 ≦ rd ≦ 0.785.
According to the first method, the diameter d of the hole 202 can be continuously changed according to the relative density rd.
Further, as a weight reduction technique, the porous body 201 having the holes 202 is used, and the size of the holes 202 is changed, whereby the weight can be reduced while maintaining a certain degree of strength. For example, if the weight of the structure is reduced by making the material of the structure thinner, the strength is significantly reduced.

(Second method)
FIG. 3 is a diagram illustrating an example of a correspondence relationship between the relative density and the porous body in the second method.
In the second method, grouping is performed for each range of relative density values, and a porous body corresponding to each group is assigned, thereby making the relative density discrete and speeding up the processing.
That is, in the second method, first, the structure analysis processing unit 102 (FIG. 1) calculates the relative density of the structure. And the part of a structure is arrange | positioned with the porous body of the group corresponded to the relative density which the porous body arrangement | positioning process part 104 (FIG. 1) calculated. By doing so, the processing speed can be increased.

In the second method, it is assumed that a first shape type with circular holes and a second shape type with square holes are prepared. Since the first shape type has rounded voids, it can prevent breakage due to concentrated stress and can be applied up to a relative density of 0.785 as described above. On the other hand, the porosity of the second shape type can be made larger than that of the first shape type. The built-in processing routine for porous body shape generation in the second method is not checked in the default setting check column 361 in the relative density-porous body data setting unit 360 described later in FIG. The program is executed by inputting a program name in the generation program setting field 362.

The function shown in FIG. 2B, the porous body data (porous body data) generated by the first method, and the porous body data for each relative density shown in FIG. Stored in the body DB 111.

[flowchart]
FIG. 4 is a flowchart showing the procedure of the layered modeling data generation process according to this embodiment.
In the following description, FIG. 1 will be referred to as appropriate.
Here, an outline of each process is shown. A detailed description of each process will be given later.
First, a setting process is performed by the input device 3 (S101). In the setting process, the additive manufacturing data generation apparatus 1 stores all data transmitted from the input device 3 in the shape DB 112 prepared for the additive manufacturing data generation process.
After the information necessary for the additive manufacturing data generation process is set on the setting screen 300 described later in FIG. 5, the determination button 370 on the setting screen 300 is selected and input by the user. Then, the information set on the setting screen 300 is transmitted from the input device 3 to the additive manufacturing data generation device 1.
When the layered modeling data generation device 1 receives the information set on the setting screen 300, the layered modeling data generation device 1 executes the processes after step S <b> 102.

First, the structure analysis processing unit 102 performs a structure analysis process (S102), and performs a stress distribution calculation process (S103).
Then, the weight reduction processing unit 103 performs the weight reduction processing (S104), and determines whether or not the result of the weight reduction processing satisfies the weight reduction conditions (S105).
If the result of step S105 does not satisfy the weight reduction condition (S105 → No), the weight reduction processing unit 103 updates the Young's modulus (S106) and returns the process to step S102.

If the result of step S105 satisfies the weight reduction condition (S105 → Yes), the weight reduction processing unit 103 performs a relative density distribution calculation process (S107).
Thereafter, the porous body arrangement processing unit 104 performs the porous body arrangement processing for arranging the porous body data corresponding to the calculated relative density in the three-dimensional shape data (S108), thereby generating the weight-reduced shape data.

(Setting process: S101 in FIG. 4)
FIG. 5 is a diagram illustrating an example of the setting screen 300 according to the present embodiment.
The setting screen 300 is a screen for the user to set data necessary for the additive manufacturing data generation process. The user can confirm the input and change of the setting value on the display of the setting screen 300 and can instruct data transmission to the additive manufacturing data generation apparatus 1.
As shown in FIG. 5, the setting screen 300 includes a shape data setting unit 310, an attribute data setting unit 320, a load data setting unit 330, a physical property value data setting unit 340, a weight reduction condition data setting unit 350, a relative density-porous material. A correspondence data setting unit 360 and a determination button 370 are provided.

In the shape data setting unit 310, settings relating to the three-dimensional shape data of the structure to be reduced in weight are performed.
The shape data setting unit 310 has an input field 311 for designating STL data of a structure by a file name, and a thumbnail image field 312 for confirming the outer shape of the STL data.

In the attribute data setting section 320, settings relating to structure attributes such as capacity, mass, material, etc. of the structure are made in the attribute data setting field 321. The attribute data is used when stress distribution and relative density are calculated.

In the load data setting unit 330, a setting relating to a load that is an external force that the structure receives during operation is performed in the load data setting field 331.
The load data includes a load type, a load position, a load magnitude, a constraint position, a constraint type, and the like.
There are types of load such as concentrated load, distributed load, and pressure. These load types are properly used depending on the external force applied to the structure, and the position of the structure to be applied is set in the load position column. Here, it is assumed that the load position is given by a node in the STL data where the load is applied.
The restraint position indicates a physical restraint of the structure, that is, a fixed position. Here, it is assumed that the fixed position (restraint position) is given by a node in the STL data. As the constraint type, it is necessary to specify six degrees of freedom in the translation direction and the rotation direction of the x-axis, y-axis, and z-axis. Here, complete fixing with all degrees of freedom fixed is set.

In the physical property value data setting unit 340, the physical property value setting field 341 performs setting related to the physical property value of the material used for manufacturing the structure. The physical property value data indicates information regarding the material in the attribute data as specific physical property values. As physical properties, density, Young's modulus, Poisson's ratio, yield stress, tensile strength, and the like are set. The physical property value is used when the structural analysis is performed based on the load data, and is used when the stress distribution generated in the structure during operation is obtained.

In the weight reduction condition data setting unit 350, the weight reduction condition used when the layered modeling data generation process is performed in the weight reduction condition data setting field 351 is set.
The weight reduction conditions include a target weight reduction mass, a weight reduction target area, an objective function, and the like. The target weight-reducing mass is for indicating how much the mass of the structure is to be reduced, and here the target is 20% reduction. Further, the lightening target area is indicated by a set of nodes in the form of three-dimensional shape data. The area to be reduced in weight is set when it is desired to previously specify an area in which the porous body is to be arranged.

The relative density-porous body data setting unit 360 sets a method used when assigning porous body data corresponding to the relative density.
The relative density-porous material correspondence setting unit 360 includes a default setting check field 361, a porous material generation program setting field 362, and the like, and settings for generating porous material data corresponding to the relative density in the STL format are performed. Is called.

In the relative density-porous material setting unit 360, the default setting check column 361 is a check column for designating whether or not to use the first method. First, a check is input to the default setting check field 361 via the input device 3. Then, the porous body arrangement processing unit 104 generates porous body data corresponding to the relative density using the built-in processing routine (first method) described with reference to FIGS. 2A to 2C. And the porous body arrangement | positioning process part 104 arrange | positions the produced | generated porous body data in three-dimensional shape data.

When the default setting check field 361 is not checked, the porous body arrangement processing unit 104 prompts the porous body generation program setting field 362 to input the file name of the porous body generation program. The porous body generation program is a program that takes a relative density as an argument and returns a porous body shape data corresponding to the relative density in an STL format. That is, the porous body generation program is a program for selecting a porous body by the second method described with reference to FIG.
The porous body generation program is an interface prepared for the user to create and incorporate. The user inputs the created porous body generation program file name in the porous body generation program setting field 362. Thereby, for example, the porous body generation program is dynamically linked, and the porous body generation program is called as a subroutine. As a result, the porous body arrangement processing unit 104 arranges the porous body data using the second method described with reference to FIG. 3 in the three-dimensional shape data.

When the data setting necessary for the additive manufacturing data generation process is completed via the setting screen 300, the user selects and inputs the determination button 370. Thereby, the set information is transmitted to the additive manufacturing data generation apparatus 1, and the process after step S102 of FIG. 4 is executed.

(Example structure)
FIG. 6 is a diagram illustrating an example of a structure to be processed. In this embodiment, an example in which the structure to be reduced in weight is a golf club head is shown.

6, at the same time that the three-dimensional shape data indicates a golf club head, the external force received during operation is a concentrated load 403 generated when a ball is hit at the center of the face surface 402. The restraint position is the connecting portion 404 between the shaft and the head, and the restraint type is complete restraint. An object to be reduced in weight is an area 401 excluding the face surface 402 in the head. Further, 64 titanium is used as a material for producing a golf club head. On the other hand, under the weight reduction conditions, the target weight reduction mass is 20% reduction of the current mass and takes strain energy in the objective function so that the strain energy becomes the minimum value, that is, the rigidity becomes the maximum value. It is set to be. In addition, it is assumed that the second shape type (see FIG. 3) of the second method is used for the arrangement method of the porous body data.

<Structural analysis process (S102 in FIG. 4) and stress distribution calculation process (S103 in FIG. 4)>
Next, the structure analysis process (S102) and the stress distribution calculation process (S103) will be described in detail.
In the structural analysis processing in step S102, the structural analysis processing unit 102 of the additive manufacturing data generation apparatus 1 performs structural analysis calculation using the three-dimensional shape data set in the setting processing. Specifically, the structure analysis processing unit 102 divides the analysis mesh into separate meshes for analysis, which are different from the elements constituting the three-dimensional shape data. Then, based on this mesh, the structural analysis processing unit 102 calculates what force is applied to which part of the structure when an external force is applied to the structure based on a predetermined load condition.
Next, in the stress distribution calculation process in step S103, the structural analysis processing unit 102 calculates the stress distribution from the analysis result calculated in the structural analysis process in step S102. Then, the structural analysis processing unit 102 stores the stress value at each location of the three-dimensional shape data in the stress distribution DB 113. Here, if, for example, general-purpose analysis software ABAQUS manufactured by Dassault Systèmes is applied as the structural analysis processing unit 102, the structural analysis processing and the stress distribution calculation processing can be easily realized.

FIG. 7 is a diagram showing the stress distribution as a result of the structural analysis process and the stress distribution calculation process using the three-dimensional shape data of the golf club head shown in FIG.
In FIG. 7, the stress distribution is displayed according to the index 511 representing the strength of the stress. From the stress distribution 501 shown in FIG. 7, it can be seen that the maximum stress is generated in the portion 502 where the ball hits, and a load transmission path exists over the base portion 503 of the shaft.

(Lightening processing: S104 in FIG. 4)
Next, in the weight reduction processing in step S104, the weight reduction processing unit 103 executes the weight reduction calculation according to the stress distribution data output in step S103 and the weight reduction conditions set in step S101. As a result, the relative density is output. That is, the weight reduction processing unit 103 calculates the relative density possible in each region of the structure based on the stress distribution data. Specifically, the weight reduction processing unit 103 obtains a load transmission path from the obtained stress distribution, and calculates a relative density distribution that satisfies the weight reduction condition.
Here, in the structure, since it is difficult to reduce the weight in a region where the stress acts largely, the relative density is close to 1. In the region where the stress hardly acts, the weight can be reduced, so the relative density is close to 0. Can be a value. In the density method for reducing the weight by such a method, a virtual material whose Young's modulus is a function of density is considered, and the density distribution in the allowable design region is determined so that the objective function is minimized. There are many commercially available general-purpose software for calculating the density distribution, which can be easily realized by applying, for example, general-purpose software TOSCA of Dassault Systèmes. If the density distribution is calculated, it is easy to calculate the relative density distribution therefrom.

(Lightweight condition determination: S105 in FIG. 4)
As described above, in the weight reduction condition determination in step S105, the weight reduction processing unit 103 performs the following calculation. That is, the weight reduction processing unit 103 calculates the mass of the structure when the structure is generated based on the relative density distribution generated in the weight reduction processing (S104). Then, the weight reduction processing unit 103 determines whether the calculation result satisfies the weight reduction condition set in step S101.
As a result of step S105, if the weight reduction condition is satisfied (S105 → Yes), the weight reduction processing unit 103 proceeds to the relative density distribution calculation processing of step S107.
If the weight reduction condition is not satisfied as a result of step S105 (S105 → No), the weight reduction processing unit 103 uses the relative density calculated in step S104 to make the Young's modulus for each element constituting the three-dimensional shape data. Is updated (S106). Thereafter, the weight reduction processing unit 103 returns the process to step S102, and executes the structural analysis process again using the updated Young's modulus.

In this way, by repeatedly executing steps S102 to S106, the additive manufacturing data generation apparatus 1 can gradually reduce the density of the structure and obtain a relative density distribution that satisfies the weight reduction condition.
It should be noted that steps S102 to S106 are repeatedly executed in the conventional techniques. However, the conventional technology needs to be repeated until the relative density becomes 0 or 1 even if the weight reduction condition is satisfied. On the other hand, the technique of the present embodiment may have an intermediate value between 0 and 1 for the relative density, so that the repetition of steps S102 to S106 can be skipped if the weight reduction condition is satisfied.

(Relative density distribution calculation processing: S107 in FIG. 4)
In step S107, the weight reduction processing unit 103 executes a relative density distribution calculation process for calculating a relative density distribution in the structure that satisfies the weight reduction condition. And the weight reduction process part 103 stores in density distribution DB114 as relative density distribution data.

FIG. 8 is a diagram showing the relative density distribution in the structure calculated by the relative density distribution extraction calculation process in step S107.
The relative density distribution shown in FIG. 8 is displayed according to the index 611 indicating the relative density. From FIG. 8, it can be seen from the relative density distribution 601 of the golf club head that the relative density is small in a region 602 that is out of the load transmission path (in FIGS. 8 to 10, what is different from FIGS. 6 and 7). Note that the orientation of the golf club head is different).

(Porous body arrangement processing: S108 in FIG. 4)
After step S107, the porous body placement processing unit 104 places porous body data based on the relative density distribution extracted in step S107. The porous body arrangement processing unit 104 generates weight reduction shape data by arranging porous body data corresponding to the calculated relative density value for each element. In other words, the porous body arrangement processing unit 104 replaces the corresponding three-dimensional shape data portion with the porous body data corresponding to the value of the relative density.
When the first method is used, the porous body arrangement processing unit 104 obtains the diameter of the porous body by the equation shown in FIG. 2B, and the relative density corresponding to the data (porous body data) of the porous body having the obtained diameter. Is replaced.
Further, when the second method is used, the porous body arrangement processing unit 104 selects a porous body having a porosity corresponding to the corresponding relative density, as shown in FIG. And the porous body arrangement | positioning process part 104 substitutes the part of the relative density which corresponds with the data (porous body data) of the selected porous body.

FIG. 9 is a diagram in which the weight-reduced shape data 701 of the weight-reduced golf club head is generated for the continuous region 602 smoothed at the portion of the relative density 0.5 in the relative density distribution in FIG. Here, the second shape type having a porosity of 30% in FIG. 3 is arranged.
In FIG. 9, only the second shape type having a porosity of 30% is shown, but actually, porous body data of each porosity corresponding to the relative density is arranged in various places.

Then, the layered modeling data generation device 1 transfers the generated weight-reduced shape data to the 3D printer device 2, and ends the operation of the layered modeling data generation device 1.

When the 3D printer apparatus 2 receives the weight-reduced shape data from the layered modeling data generation apparatus 1, the 3D printer apparatus 2 starts the layered modeling process and creates a layered modeling of the weight-reduced structure.

FIG. 10 is a diagram illustrating an example of a weight-reduced golf club head that is layered and formed based on the weight-reduced shape data generated by the 3D printer apparatus 2.
In the weight-reduced golf club head (product) 801 shown in FIG. 10, it can be seen that a porous body corresponding to the relative density is generated at a location corresponding to the region 602 in FIG.
As in FIG. 9, FIG. 10 shows only where the second shape type with a porosity of 30% is arranged, but in reality, porous bodies with various porosity according to the relative density are in various places. Be placed. Even when only one kind of porous body having a porosity is used, this porous body is arranged based on the relative density, so that it differs from the conventional methods in which the relative density is only 0 or 1.

[3D printer device 2]
FIG. 11 is a conceptual diagram of a general 3D printer apparatus 2.
11, the 3D printer apparatus 2 includes a carbon dioxide laser oscillator 910, a collimator 911, a galvano operation device 913, a condensing lens 914, and a first lifting table 921. Further, the 3D printer apparatus 2 includes a first lifting mechanism 923, a reference table 912, a second lifting table 922, a second lifting mechanism 924, and a squeegee 916.
In FIG. 11,

reference numerals

917 and 918 denote metal powders. Reference numeral 919 denotes a powder sintered part being shaped. Reference numeral 920 indicates a base for supporting the powder sintered component 919.

The carbon dioxide laser oscillator 910 generates pulsed laser light 915. The collimator 911 adjusts the beam diameter of the laser light 915. The galvano operating device 913 guides the laser beam 915 to a predetermined place. The condensing lens 914 condenses the laser beam 915 and locally sinters the powder.
The first lifting table 921 sets the metal powder 917 to a predetermined height as needed. The first lifting mechanism 923 moves the first lifting table 921 up and down.
The reference table 912 determines the position of the laminated surface of the metal powder 918.
The second elevating table 922 descends from the height of the reference table 912 as needed by the thickness of the metal powder 918 to be laminated.
The second lifting mechanism 924 moves the second lifting table 922 up and down.
The squeegee 916 reciprocates between the first lifting table 921 and the second lifting table 922. As a result, the metal powder 917 on the first lifting table 921 is conveyed to the second lifting table 922, and at the same time, the metal powder 918 is stretched. By doing so, the squeegee 916 can spread the metal powder 918 thinly with a predetermined thickness.

The areas of the first lift table 921 and the second lift table 922 are equal. Accordingly, if the first lifting table 921 and the second lifting table 922 are raised and lowered at the same distance, the amount of the metal powder 917 supplied from the first lifting table 921 and the metal powder 918 received by the second lifting table 922 are received. The amount of is equal.
Each time the second lifting table 922 is lowered, the powder sintered component 919 is gradually shaped. The second lifting table 922 moves down until the position of the reference table 912 reaches the modeling area 925. In the 3D printer 2, the beam diameter of the pulsed laser beam 915 emitted from the carbon dioxide laser oscillator 910 is adjusted by the collimator 911. Thereafter, the laser beam 915 is guided to a predetermined place by the galvano operating device 913 and is condensed by the condenser lens 914. Then, the condensed laser beam 915 is irradiated to the metal powder 918 laminated on the powder sintered component 919.

The heat source of the laser beam 915 may be an electron beam device assuming a 400 watt laser device. Here, the laser beam 915 has a beam spot diameter of 0.5 mm, a pulse width of 3.0 ms, an operation speed of 9 mm / s, and an oscillation frequency of 90 Hz.
For the metal powders 917 and 918, 64 titanium particles having a particle diameter of 20 μm to 45 μm are used. 64 titanium is a metal powder containing 6% aluminum (Al) and 4% vanadium (V) by mass fraction.

[effect]
FIG. 12 explains the effect of this embodiment.
The graph in FIG. 12 shows the calculation cost when the golf club head is reduced in weight by the conventional method (comparative example).
In FIG. 12, the horizontal axis indicates the number of calculations required until the weight-reduced shape is calculated. The right side of the vertical axis shows the strain energy of the objective function, and the left side of the vertical axis shows the relative mass of the structure.
The graph of FIG. 12 shows a strain energy change 1001 and a relative mass change 1002 for each number of weight reduction calculations.

From the graph shown in FIG. 12, the values of the strain energy change 1001 and the relative mass change 1002 do not change after 12 times. This indicates that the target “minimum strain energy” and “mass 20% reduction” are achieved when the number of calculations is 12. Here, “mass 20% reduction” is a weight reduction condition in this simulation.

However, the weight-reduced shape that can be obtained with 12 calculations includes a region having an intermediate density that is not 1 or 0, and it is difficult to produce a product by the conventional manufacturing methods. Therefore, in the conventional manufacturing method, the calculation is performed so that the relative density becomes 0 or 1 after the calculation is 12 times or more. That is, the portion where the relative density is 0 is increased or decreased, and it is further determined whether or not the current state satisfies the weight reduction condition.

As described above, in the conventional methods, it is necessary to repeat the calculation until the intermediate density is eliminated, and to calculate until a distribution having a relative density of 0 or 1 is obtained. Under the simulation conditions of FIG. 12, 55 calculations are required.
As is apparent from the graph of FIG. 12, most of the number of calculations in the conventional method is spent on calculating so that the relative density is 0 or 1. Specifically, every time the size of the portion where the relative density is 0 is changed, structural analysis is performed to obtain a stress distribution.

In this embodiment, since the porous body according to the relative density is arranged, the calculation can be completed at the time when the number of calculations is 12 in FIG.
In the present embodiment, the weight reduction is realized by utilizing the layered modeling of the 3D printer apparatus 2 and disposing a porous body in an intermediate density region. Accordingly, as shown in FIG. 12, the relative density distribution of the target lightweight golf club head can be obtained with 12 calculations. The porous body data corresponding to the relative density may be arranged in the three-dimensional shape data. This is about 1/5 of the conventional number of calculations. As described above, the additive manufacturing data generation apparatus 1 according to the present embodiment can significantly reduce the calculation cost as compared with the conventional techniques.

[Comparison with comparative example]
FIG. 13 shows the relative density distribution of the golf club head obtained by the conventional method (comparative example). Here, in the method so far, as described in FIG. 12, it is a method in which the portion with the lightening is obtained by repeatedly calculating until the relative density becomes 0 or 1.
The relative density distribution in FIG. 13 is displayed according to an index 1111 indicating the relative density.
Here, the relative density distribution 1101 of the golf club head shown in FIG. 13 and the relative density distribution 601 of the golf club head including the intermediate density shown in FIG. 8 are compared. As a result, it can be seen that the distribution of the relative density is greatly different in the region 1102 outside the load transmission path. In the relative density distribution shown in FIG. 13, a region 1121 having a relative density “1” and a region 1122 having a relative density “0” are clearly shown, suggesting a portion to be thinned.

FIGS. 14 and 15 are views showing a weight-reduced golf head created by the 3D printer apparatus 2 by the conventional method (comparative example).
FIG. 14 shows the shape extracted from the relative density distribution shown in FIG. 13 and the weight-reduced golf club head shape 1201 created by the 3D printer device 2. As shown in FIG. 14, for example, the portions indicated by

reference numerals

1202 and 1203 have uneven edges and have irregularities. In addition, a member indicated by reference numeral 1204 is missing.
This is because the structure is formed based on a mesh larger than the elements used in the structural analysis.

For this reason, the conventional methods require edge smoothing. The smoothing process is often performed manually. The portions where the irregularities such as

reference numerals

1202 and 1203 in FIG. 14 exist become

smooth edges

1302 and 1303 as shown in FIG. 15 by the smoothing process. Further, in FIG. 14, a part such as reference numeral 1204 where the member is missing becomes a member as indicated by reference numeral 1304 when the user manually supplements the member. By such a smoothing process, a structure 1301 having a smooth edge is obtained. However, since it is not known whether the necessary strength has been maintained after such a manual smoothing process has been performed, the 3D shape data is manually corrected once again to perform structural analysis. There is a need to do.

In this embodiment, the porous body data generated based on the elements of the three-dimensional shape data that is unrelated to the mesh for structural analysis is arranged in the three-dimensional shape data. For this reason, the unevenness | corrugation derived from the mesh in the case of a structural analysis, or the part divided | segmented does not arise. For this reason, in this embodiment, the smoothing process of an edge becomes unnecessary and it can improve the modeling speed of a structure.

Also, in the conventional technology, the calculation is repeated until the relative density becomes 0 or 1, and the region where the relative density is 0 is extracted. In contrast, in the additive manufacturing data generation apparatus 1 according to the present embodiment, the porous body arrangement processing unit 104 converts the porous body data corresponding to the relative density into three-dimensional shape data based on the relative density (feature amount). Lightening by placing. By doing in this way, it is not necessary to repeat the calculation until the relative density becomes 0 or 1, and the calculation cost can be reduced.

In this embodiment, the density distribution of the substance is calculated based on the state of stress, and the porous body data corresponding to this density distribution is arranged in the three-dimensional shape data. The additive manufacturing system Z of the present embodiment can be applied to an object to which force is applied in this way.
In addition, since the relative density distribution is used as the density distribution, it is possible to handle the structures having different densities in a unified porous body shape.

It should be noted that the structures manufactured by the conventional methods all have the same size in the area to be reduced in weight. On the other hand, the structure manufactured by the method of the present embodiment has pores having different sizes for each place because porous bodies having different pore sizes are arranged according to the relative density.

In this embodiment, the porous body is arranged based on the relative density based on the stress distribution, but not limited to this, based on the density of physical property information based on physical property characteristics such as heat distribution and current distribution. A porous body may be disposed.
Further, in the present embodiment, the golf club head is exemplified as an object to be reduced in weight. However, the present invention is not limited to this, and any mechanical part such as an engine piston or a shaft that can reduce the weight may be used. . As a technical field to which the weight reduction conversion processing according to the present embodiment is applied, the automobile, electric power, and aerospace fields can be considered.

In the present embodiment, the porous body to be arranged is determined based on the relative density, but the porous body may be determined based on the density instead of the relative density. Further, the density may not be a stress value or the like.

The present invention is not limited to the above-described embodiment, and includes various modifications. For example, the above-described embodiment has been described in detail for easy understanding of the present invention, and is not necessarily limited to having all the configurations described. Further, it is possible to add, delete, and replace other configurations for a part of the configuration of the present embodiment.

Each of the above-described configurations, functions, units 101 to 104, DBs 111 to 115, etc. may be realized by hardware by designing a part or all of them with, for example, an integrated circuit. Further, as shown in FIG. 1, the above-described configurations, functions, and the like may be realized by software by interpreting and executing a program that realizes each function by a processor such as the CPU 120. Information such as programs, tables, and files for realizing each function is stored in an HD (Hard Disk), a memory, a recording device such as an SSD (Solid State Drive), an IC (Integrated Circuit) card, It can be stored in a recording medium such as an SD (Secure Digital) card or a DVD (Digital Versatile Disc).
In each embodiment, control lines and information lines are those that are considered necessary for explanation, and not all control lines and information lines are necessarily shown on the product. In practice, it can be considered that almost all configurations are connected to each other.

DESCRIPTION OF SYMBOLS 1 Layered modeling data production | generation apparatus 2 3D printer apparatus (modeling part)
3 Input device 101 Processing unit 102 Structure analysis processing unit (physical property information estimation unit, feature amount distribution calculation unit)
103 Weight reduction processing part 104 Porous body arrangement | positioning processing part (porous body arrangement | positioning part)
111 Porous DB (storage unit)
112 Shape DB
113 Stress distribution DB
114 Density distribution DB
115 Lightweight shape DB
202 Porous body 501 Stress distribution 601 Relative density distribution 801 Light weight golf club head (product)

Claims

A storage unit storing feature quantity-porous body information in which a feature quantity in a structure to be modeled by additive manufacturing is associated with a degree of the void in a porous body having a void;
A physical property information estimation unit for estimating information related to physical properties in the structure;
A feature amount distribution calculating unit that calculates a feature amount distribution that is a distribution of the feature amount in the structure based on the information on the estimated physical property;
Based on the feature quantity-porous body information, the porosity of the porous body corresponding to the calculated distribution of the feature quantity is determined, and the data of the structure is replaced with the determined data of the porous body A placement section;
An additive manufacturing data generation apparatus characterized by comprising:
Information on the physical properties is a state of stress,
The layered modeling data generation apparatus according to claim 1, wherein the distribution of the feature amount is a density distribution of a substance.
The additive manufacturing data generation apparatus according to claim 2, wherein the density distribution of the substance is a relative density distribution that is a relative density distribution with respect to an original density of the material of the substance.
2. The additive manufacturing data generation apparatus according to claim 1, wherein the degree of voids in the porous body is a size of a hole in the porous body.
The layered modeling data generation apparatus according to claim 4, wherein the hole is a circular hole.
The additive manufacturing data generation apparatus according to claim 4, wherein the hole is a square hole.
5. The additive manufacturing data generation apparatus according to claim 4, wherein the feature quantity-porous body information is a function having the feature quantity as an independent variable and a pore size in the porous body as a dependent variable.
5. The additive manufacturing data generation according to claim 4, wherein in the feature quantity-porous body information, the feature quantity is divided into predetermined groups, and the size of the hole in the porous body is determined in each group. apparatus.
A storage unit storing feature quantity-porous body information in which a feature quantity in a structure to be modeled by additive manufacturing is associated with a degree of the void in a porous body having a void;
A physical property information estimation unit for estimating information related to physical properties in the structure;
A feature amount distribution calculating unit that calculates a feature amount distribution that is a distribution of the feature amount in the structure based on the information on the estimated physical property;
Based on the feature quantity-porous body information, the porosity of the porous body corresponding to the calculated distribution of the feature quantity is determined, and the data of the structure is replaced with the determined data of the porous body A placement section;
Based on data obtained by replacing the data of the structure with the data of the porous body, a modeling unit that models the structure by the additive manufacturing, and
An additive manufacturing system characterized by comprising:
A storage unit storing feature quantity-porous body information in which a feature quantity in a structure to be modeled by additive manufacturing is associated with a degree of the void in a porous body having a void;
A physical property information estimation unit for estimating information related to physical properties in the structure;
A feature amount distribution calculating unit that calculates a feature amount distribution that is a distribution of the feature amount in the structure based on the information on the estimated physical property;
Based on the feature quantity-porous body information, the porosity of the porous body corresponding to the calculated distribution of the feature quantity is determined, and the data of the structure is replaced with the determined data of the porous body A placement section;
Based on data obtained by replacing the data of the structure with the data of the porous body, a modeling unit that models the structure by the additive manufacturing, and
A product formed by the additive manufacturing system.