Thickness prediction device and thickness prediction method for surface-modified layer

Abstract

The present invention predicts the thickness of a surface-modified layer without confirming before processing or without adding an inspection step during processing or after processing.　This thickness prediction device for a surface-modified layer of a workpiece formed by using a laser comprises: a laser emission condition acquisition unit that acquires laser emission conditions including at least the processing speed and a laser output condition at each position on the surface of the workpiece; a material information acquisition unit that acquires the material information about the workpiece; and a surface-modified layer thickness prediction unit that predicts the thickness of the surface-modified layer at each position of the workpiece on the basis of the laser emission conditions and the material information.

Description

Surface modification layer thickness prediction device and thickness prediction method

[0001] The present disclosure relates to an apparatus and method for predicting the thickness of a surface modified layer, and more particularly to an apparatus and method for predicting the thickness of a surface modified layer of a workpiece formed using a laser.

[0002] Methods for modifying the surface of a workpiece by irradiating the surface of the workpiece with a laser are described in, for example, Patent Documents 1 and 2.

[0003] Patent Document 1 describes a method for manufacturing a surface-modified substrate, which involves irradiating the surface of a metal substrate with a laser to modify the surface of the substrate. Specifically, Patent Document 1 describes a method for manufacturing a surface-modified substrate, which includes a step of providing a resin layer that transmits laser light on the surface of the metal substrate, and a step of irradiating the substrate surface with a laser through the resin layer to melt the surface of the substrate and thermally decompose the resin layer by the heat of the substrate.

[0004] Patent Document 2 describes a method for producing a surface-modified member that can obtain a thick modified layer that has high adhesion to the substrate and is reduced in contamination with substrate components. Specifically, Patent Document 2 describes a method for producing a surface-modified member that includes a step of forming a thermal sprayed coating on the substrate, a step of irradiating the surface of the thermal sprayed coating with a high-energy beam to melt and solidify the entire thermal sprayed coating and a portion of the substrate in the thickness direction to form a densified modified layer, a step of forming a thermal sprayed coating on the modified layer formed just before, and a step of irradiating the surface of the thermal sprayed coating with a high-energy beam to melt and solidify the entire thermal sprayed coating and a portion of the modified layer formed just before to form a densified modified layer.

[0005] International Publication No. 2016 / 103385 Japanese Patent Application Laid-Open No. 2019-163550

[0006] Surface modification of workpieces using a laser includes, for example, laser hardening and laser cladding (coating), which are used to partially strengthen mechanical components. In surface modification processing, the thickness of the surface modification layer is important, and a thickness prediction device and a thickness prediction method that can predict the thickness of the surface-modified layer are desired.

[0007] A first representative aspect of the present disclosure is a thickness prediction device for a surface modification layer of a workpiece formed using a laser, comprising: a laser irradiation condition acquisition unit that acquires laser irradiation conditions including at least a processing speed and a laser output condition for each position on the surface of the workpiece; a material information acquisition unit that acquires material information of the workpiece; and a surface modification layer thickness prediction unit that predicts the thickness of the surface modification layer at each position on the workpiece based on the laser irradiation conditions and the material information.

[0008] A second representative aspect of the present disclosure is a method for predicting the thickness of a surface modification layer formed using a laser, in which a computer serving as a device for predicting the thickness of a surface modification layer of a workpiece performs the following processes: acquiring laser irradiation conditions including at least a processing speed and a laser output condition for each position on the surface of the workpiece; acquiring material information of the workpiece; and predicting the thickness of the surface modification layer at each position on the workpiece based on the laser irradiation conditions and the material information.

[0009] 1 is a block diagram showing an example of a configuration of a thickness prediction device according to a first embodiment of the present disclosure; FIG. 1 is an explanatory diagram illustrating laser hardening; FIG. 2 is a diagram illustrating a state in which a laser head irradiates a workpiece with a laser while the workpiece is moved relative to the laser head; FIG. 3 is a cross-sectional view showing the thickness of a surface modified layer formed on a workpiece; FIG. 4 is a diagram illustrating an example of a display image in which the degree of thickness of the surface modified layer is displayed by changing the display mode of the workpiece; FIG. 5 is an explanatory diagram illustrating laser cladding; FIG. 6 is a diagram illustrating a state in which a laser head irradiates a workpiece with a laser while the workpiece is moved relative to the laser head and powder is supplied; FIG. 7 is a cross-sectional view showing the thickness of a surface modified layer formed on a workpiece; FIG. 8 is a diagram illustrating a method for calculating a laser irradiation area per unit time by laser irradiation; FIG. 9 is a perspective view showing a workpiece divided into meshes; FIG. 10 is a diagram showing a heat flux applied at time t; FIG. 11 is a diagram showing a temperature distribution in a cross section of a workpiece; FIG. 12 is a cross-sectional view showing the thickness of a surface modified layer formed on a workpiece; 10 is a block diagram showing a configuration example of a thickness prediction device according to a third embodiment of the present disclosure; FIG. 11 is a block diagram showing a configuration example of a thickness prediction device according to a fourth embodiment of the present disclosure; FIG. 12 is a diagram showing an example of displaying the thickness of a surface modification layer at a specified position;

[0010] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. The method of surface modification is not particularly limited as long as the embodiment of the present disclosure is a thickness prediction device and a thickness prediction method for surface modification of a workpiece using a laser. However, the following description will be directed to laser hardening and laser cladding (coating).

[0011] First Embodiment FIG. 1 is a block diagram showing an example configuration of a thickness prediction device according to a first embodiment of the present disclosure. As shown in FIG. 1, a thickness prediction device 10 includes a laser irradiation condition acquisition unit 11, a material information acquisition unit 12, a surface modification layer thickness prediction unit 13, and a display unit 14. The display unit 14 is provided as needed. The display unit 14 may be replaced with a component capable of outputting information including the thickness of the surface modification layer to a user. For example, the display unit 14 may be replaced with a printer or a communication unit that transmits information to an external device.

[0012] The laser irradiation condition acquisition unit 11 acquires laser irradiation conditions including the processing speed and laser output conditions at each position on the workpiece surface. The processing speed refers, for example, to the speed at which the workpiece and the laser head that irradiates the workpiece with a laser are moved relative to each other. The laser output conditions are, for example, laser output and spot diameter. In the case of laser cladding, the laser irradiation conditions include the processing speed and laser output conditions as well as additional material supply conditions. If the additional material is a powder such as metal powder, the additional material supply condition is, for example, the powder supply amount. The powder supply amount is the amount of powder supplied per unit time to the workpiece to be irradiated with the laser. The laser oscillator receives an output command to generate a laser, and the laser head focuses the laser and irradiates it on the workpiece.

[0013] The material information acquisition unit 12 acquires material information of the workpiece. The material indicates at least one of the use, composition, physical properties, and mechanical properties. For example, if the material information indicates S45C, this indicates that S45C is a type of carbon steel for machine structures and is a medium-carbon steel material with a carbon content of 0.45%.

[0014] The surface modification layer thickness prediction unit 13 predicts the thickness of the surface modification layer at each position on the workpiece based on the laser irradiation conditions acquired from the laser irradiation condition acquisition unit 11 and the material information acquired from the material information acquisition unit 12. For example, in the case of hardening, the thickness of the surface modification layer is the depth at which the hardening temperature is reached, and in the case of laser cladding, it is the thickness of the heat-affected zone affected by heat from the surface of the workpiece plus the thickness of the cladding zone.

[0015] The display unit 14 displays the thickness of the surface modification layer predicted by the surface modification layer thickness prediction unit 13. The display unit 14 is, for example, a liquid crystal display device, and displays the thickness of the surface modification layer as a numerical value. The display unit 14 may also display the degree of thickness of the surface modification layer by changing the display mode of the workpiece.

[0016] Hereinafter, a method for the surface modification layer thickness prediction unit 13 to predict the thickness of the surface modification layer at each position on the workpiece will be described.

[0017] (First Method) The first method is a method for predicting the thickness of a surface modification layer in the case of laser hardening using a table containing experimentally determined information. FIG. 2 is an explanatory diagram illustrating laser hardening. As shown in FIG. 2, a laser is applied to a workpiece 30, such as a metal, to heat the surface. The laser then moves relative to the workpiece 30, causing the workpiece 30 to self-cool and drop in temperature, resulting in hardening. For example, as shown in FIG. 3, a laser is irradiated onto the workpiece 30 from a laser head 20 while the workpiece 30 is moved at a processing speed. The thickness D of the surface modification layer of the workpiece 30, shown in the cross-sectional view of FIG. 4, is determined based on the laser irradiation conditions and the material information of the workpiece. The thickness D of the surface modification layer is the vertical length (depth) from the surface of the workpiece to the hardening temperature.

[0018] The surface modification layer thickness prediction unit 13 includes a memory unit that stores a table showing the relationship between experimentally determined laser irradiation conditions and material information and the thickness of the surface modification layer. Specifically, the memory unit stores a table listing the processing speed (m / sec), laser output (W), spot diameter (m), material information, and the thickness of the surface modification layer. As already explained, the processing speed, laser output, and spot diameter are laser irradiation conditions. The material information is, for example, S45C. The surface modification layer thickness prediction unit 13 references the table to determine the thickness of the surface modification layer corresponding to the acquired laser irradiation conditions and material information.

[0019] The display unit 14 displays the thickness of the surface-modified layer obtained by the method described above. The display unit 14 displays the thickness of the surface-modified layer, for example, by displaying the thickness of the surface-modified layer numerically or by displaying the degree of thickness of the surface-modified layer by changing the display mode of the workpiece. In addition to the thickness of the surface-modified layer, the display unit 14 may also display at least one of the laser irradiation conditions and material information.

[0020] The display unit 14 displays the thickness of the surface modification layer numerically, for example, "The thickness of the surface modification layer is 1 mm." FIG. 5 shows an example of a display image that displays the degree of thickness of the surface modification layer by changing the display mode of the workpiece. In FIG. 5, assuming the thickness range of the surface modification layer is 0 to 1 mm, the region from 0.8 mm to 1 mm is shown as a black area AR1, and the region from 0.6 mm to 0.8 mm is shown as a hatched area AR2. In FIG. 5, the degree of thickness of the surface modification layer is shown in two display modes (black area and hatched area), but three or more thickness levels, for example, 0.8 mm to 1 mm, 0.6 mm to 0.8 mm, and 0.4 mm to 0.6 mm, may be displayed in three or more display modes. The change in display mode may also be indicated by color. For example, the region from 0.8 mm to 1 mm may be shown in red, the region from 0.6 mm to 0.8 mm in orange, and the region from 0.4 mm to 0.6 mm in yellow.

[0021] (Second Method) The second method is a method for predicting the thickness of a surface modification layer in the case of laser cladding (coating) using a table listing experimentally determined information. FIG. 6 is an explanatory diagram illustrating laser cladding. As shown in FIG. 6, laser cladding is performed by using a laser as a heat source to melt powder such as metal powder and depositing the same or a different material on the surface of a workpiece 31. As shown in FIG. 6, a deposit 31A is formed by laser cladding. A molten pool 31C is formed by laser irradiation, and a heat-affected zone 31B is formed by cooling.

[0022] As shown in Fig. 7, when a laser is irradiated from the laser head 20 to the workpiece 31 at a predetermined processing speed while powder is supplied, the thickness D1 of the surface modified layer shown in Fig. 8 is determined by the laser irradiation conditions, including the amount of powder supplied, and the material information of the workpiece. The thickness D1 of the surface modified layer is the sum of the thickness of the heat-affected zone 31B from the surface of the workpiece to the point where the heat influence reaches, and the thickness of the build-up zone 31A.

[0023] The surface modification layer thickness prediction unit 13 includes a memory unit that stores a table showing the relationship between experimentally determined laser irradiation conditions, including powder supply amount, and material information, and the thickness of the surface modification layer. Specifically, the memory unit stores a table listing the processing speed (m / sec), laser output (W), spot diameter (m), powder supply amount (g / sec), material information, and surface modification layer thickness. As already explained, the processing speed, laser output, and spot diameter are laser irradiation conditions. The material information is, for example, S45C. The surface modification layer thickness prediction unit 13 references the table to determine the thickness of the surface modification layer corresponding to the acquired laser irradiation conditions, including powder supply amount, and material information.

[0024] As with the first method described above, the display unit 14 displays the thickness of the surface modification layer by displaying the thickness of the surface modification layer numerically or by displaying the degree of thickness of the surface modification layer by changing the display mode of the workpiece.

[0025] (Third Method) In the third method, in the case of laser hardening, the thickness of the surface modified layer is predicted by calculation using the laser irradiation conditions and material information. The surface modified layer thickness prediction unit 13 first calculates the heat flux q based on the laser irradiation conditions.

[0026] FIG. 9 is a diagram showing a method for calculating the laser irradiation area per unit time by laser irradiation. As shown in FIG. 9, the laser head 20 moves relative to the workpiece 30 at a processing speed v, and the laser spot moves at the processing speed v. The surface modification layer thickness prediction unit 13 multiplies the processing speed v by the spot diameter d of the laser spot to calculate the laser irradiation area S per unit time (S = v × d). The surface modification layer thickness prediction unit 13 also multiplies the laser output LP by the thermal absorptivity AB to calculate the heat input P per unit time (P = LP × AB). The surface modification layer thickness prediction unit 13 then divides the heat input P by the laser irradiation area S to calculate the heat flux q (q = P / S). The thermal absorptivity AB is included in the material information.

[0027] Next, the surface modification layer thickness prediction unit 13 calculates the temperature distribution using the finite element method. Methods for calculating the temperature distribution using the finite element method are described, for example, in https: / / www.jstage.jst.go.jp / article / imono / 63 / 1 / 63_1_32 / _pdf / -char / ja and https: / / www.jstage.jst.go.jp / article / jjasnaoe1968 / 1984 / 156 / 1984_156_406 / _pdf / -char / en. Specifically, as shown in FIG. 10 , the surface modification layer thickness prediction unit 13 divides the workpiece into meshes and discretizes the heat conduction equation shown in Equation 1 (hereinafter, Equation 1). The thermal conductivity κ, density ρ, and specific heat c are included in the material information.

[0028] Next, the surface modification layer thickness prediction unit 13 provides a condition for providing a heat flux q only within the spot range on the surface of the workpiece as a boundary condition of the discretized heat conduction equation. Figure 11 is a diagram showing the heat flux provided at time t. The surface modification layer thickness prediction unit 13 solves the discretized heat conduction equation for each mesh element, calculates the temperature of each element, and calculates the temperature distribution. Figure 12 is a diagram showing the temperature distribution on the cross section of the workpiece 30. As shown in Figure 12, the temperature decreases with increasing distance from the surface.

[0029] The surface modification layer thickness prediction unit 13 determines the depth at which the hardening temperature is reached from the calculated temperature distribution, and sets the thickness of the surface modification layer as the thickness. Figure 13 is a cross-sectional view showing the thickness of the surface modification layer formed on the workpiece. The thickness D2 of the surface modification layer of the workpiece 30 shown in the cross-sectional view of Figure 13 is determined by the laser irradiation conditions and material information of the workpiece.

[0030] Next, the thickness prediction method of the thickness prediction device 10 will be described using a flowchart. Fig. 14 is a flowchart showing an example of the operation of the thickness prediction method of the thickness prediction device 10. Fig. 14 shows an example of the operation of the thickness prediction device 10 in the case of laser hardening, but the operation in the case of laser cladding is similar.

[0031] In step S11, the laser irradiation condition acquisition unit 11 determines whether or not it is possible to acquire laser irradiation conditions including the processing speed and laser output conditions at each position on the workpiece surface. If the laser irradiation condition acquisition unit 11 can acquire the laser irradiation conditions ("YES" in step S11), it acquires the laser irradiation conditions and outputs the acquired laser irradiation conditions to the surface modification layer thickness prediction unit 13, and then the material information acquisition unit 12 performs the operation of step S12. If the laser irradiation condition acquisition unit 11 cannot acquire the laser irradiation conditions ("NO" in step S11), it performs the process of step S11 again.

[0032] In step S12, the material information acquisition unit 12 determines whether or not material information of the workpiece can be acquired. The material information is, for example, S45C. If the material information acquisition unit 12 can acquire the material information ("YES" in step S12), it acquires the material information and outputs the acquired material information to the surface modification layer thickness prediction unit 13, and then the surface modification layer thickness prediction unit 13 performs the operation of step S13. If the material information acquisition unit 12 cannot acquire the material information ("NO" in step S12), it performs the processing of step S12 again. Step S12 may be performed before step S11 or may be performed in parallel with step S11.

[0033] In step S13, the surface modification layer thickness prediction unit 13 predicts the thickness of the surface modification layer at each position on the workpiece based on the laser irradiation conditions and material information.

[0034] In step S14 , the display unit 14 displays the thickness of the surface-modified layer predicted by the surface-modified-layer thickness prediction unit 13 .

[0035] According to the thickness prediction device 10 of this embodiment described above, the thickness of the surface modification layer can be predicted without adding any check before processing or any inspection process during or after processing.

[0036] Second Embodiment FIG. 15 is a block diagram showing an example configuration of a thickness prediction device according to a second embodiment of the present disclosure. As shown in FIG. 15 , the thickness prediction device 10A includes, in addition to the configuration of the thickness prediction device 10, a CNC (Computerized Numerical Control) data storage unit 15, a machining simulation execution unit 16, and a workpiece placement information acquisition unit 17. The CNC data storage unit 15 stores CNC data including parameter settings and machining programs. The parameter settings include, for example, parameter settings related to speed control. An example of a parameter setting related to speed control is the time constant for cutting feed acceleration / deceleration for each of the X-axis, Y-axis, and Z-axis. FIG. 16 shows an example of a machining program. In the machining program shown in FIG. 16 , S represents a power command (W), P represents a frequency command (Hz), Q represents a duty command (%), and F represents a feed rate command (mm / min).

[0037] The machining simulation execution unit 16 executes a machining simulation based on the CNC data and creates point sequence data including at least coordinate values ​​on the machining path, a feed rate, and laser output conditions. In the case of laser cladding, the machining simulation execution unit 16 creates point sequence data including at least coordinate values ​​on the machining path, a feed rate, laser output conditions, and additional material supply conditions.

[0038] The workpiece placement information acquisition unit 17 acquires workpiece placement information including at least the shape of the workpiece and the relative position between the workpiece and the machining path. The shape of the workpiece can be obtained from CAD (computer-aided design) / CAM (computer-aided manufacturing). The relative position between the workpiece and the machining path can be determined as follows. Generally, in machining setup, after the workpiece is placed, the workpiece origin at the center of the workpiece relative to the machining origin is measured using a touch probe or the like, and the measurement result is used to set a coordinate system offset (workpiece coordinate system offset). This offset is the relative position between the workpiece and the machining path. In FIG. 17, the relative position corresponds to the relative position (x', y', z'). FIG. 18 is a diagram showing the machining path relative to the machining origin.

[0039] The laser irradiation condition acquisition unit 11 calculates the laser irradiation conditions on the surface of the workpiece based on the point sequence data and the workpiece placement information.

[0040] According to the thickness prediction device 10A described above, the thickness of the surface modified layer can be predicted from the results of the processing simulation before processing.

[0041] (Third embodiment) Fig. 19 is a block diagram showing an example configuration of a thickness prediction device according to a third embodiment of the present disclosure. As shown in Fig. 19, compared to the configuration of the thickness prediction device 10A, the thickness prediction device 10B excludes the CNC data storage unit 15 and the machining simulation execution unit 16 and adds an operation data acquisition unit 18. The operation data acquisition unit 18 acquires operation data including at least coordinate values, feed speeds, and laser output conditions obtained during machining. In the case of laser cladding, the operation data acquisition unit 18 acquires operation data including at least coordinate values, feed speeds, laser output conditions, and additional material supply conditions obtained during machining.

[0042] The laser irradiation condition acquisition unit 11 calculates the laser irradiation conditions on the surface of the workpiece based on the operation data and the workpiece placement information.

[0043] According to the thickness prediction device 10B described above, the thickness of the surface modified layer can be predicted from the operation data during or after processing.

[0044] 20 is a block diagram showing an example configuration of a thickness prediction device according to a fourth embodiment of the present disclosure. As shown in FIG. 20 , a thickness prediction device 10C includes a designated position specifying unit 19 in addition to the configuration of the thickness prediction device 10. The designated position specifying unit 19 specifies a position on the surface of the workpiece. The position on the surface of the workpiece is specified by being input by a user using an input device such as a keyboard or a touch panel on a liquid crystal display device, but the designated position may also be stored in advance in a storage unit and specified.

[0045] The display unit 14 displays the thickness of the surface modification layer at the specified position. Fig. 21 is a diagram showing an example of displaying the thickness of the surface modification layer at the specified position. Fig. 21 shows that the thickness of the surface modification layer at the specified position is 1.5 mm from the surface.

[0046] According to the thickness prediction device 10C described above, it is possible to predict the thickness of the surface modified layer at the specified position.

[0047] In each of the above-described embodiments, the thickness prediction device can be realized by hardware, software, or a combination thereof to realize the functional blocks included in the thickness prediction device. Here, "realized by software" means that the device is realized by a computer reading and executing a program. To realize the components included in the thickness prediction device by software or a combination thereof, the thickness prediction device includes a central processing unit (CPU) or other such device. The processing unit functions as an execution unit. The thickness prediction device also includes an auxiliary storage device such as a hard disk drive (HDD) that stores various control programs such as application software or an operating system (OS), and a main storage device such as a random access memory (RAM) that stores data temporarily required for the processing device to execute the programs.

[0048] The thickness prediction device has an arithmetic processing unit that reads application software or an OS from the auxiliary storage device, and then loads the loaded application software or OS into the main storage device while performing arithmetic processing based on the application software or OS. Furthermore, the thickness prediction device controls various hardware components based on the results of this calculation. This realizes the functional blocks of this embodiment.

[0049] The components included in the thickness prediction device can be realized by hardware including electronic circuits, etc. When the thickness prediction device is configured by hardware, some or all of the functions of the components included in the thickness prediction device can be configured by an integrated circuit (IC) such as an ASIC (Application Specific Integrated Circuit), a gate array, an FPGA (Field Programmable Gate Array), or a CPLD (Complex Programmable Logic Device).

[0050] The program can be stored and supplied to a computer using various types of non-transitory computer-readable media. Non-transitory computer-readable media include various types of tangible storage media. Examples of non-transitory computer-readable media include magnetic recording media (e.g., hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD-ROMs (Read Only Memory), CD-Rs, CD-R / Ws, and semiconductor memories (e.g., mask ROMs, PROMs (Programmable ROMs), EPROMs (Erasable PROMs), flash ROMs, and RAMs (Random Access Memory)). The program may also be supplied to the computer by various types of transient computer readable media.

[0051] According to the thickness prediction device and thickness prediction method of the present disclosure, including the embodiments described above, the thickness of the surface modification layer can be predicted without any additional confirmation before processing or inspection processes during or after processing.

[0052] Although the above-described embodiments are preferred embodiments of the present invention, the scope of the present invention is not limited to the above-described embodiments, and various modifications can be made without departing from the spirit of the present invention. For example, the thickness prediction device and thickness prediction method used in laser hardening or laser cladding can also be applied to thermal spraying, and can also be applied to the manufacturing methods described in Patent Documents 1 and 2.

[0053] The following supplementary note is further disclosed regarding the above embodiment: (Supplementary note 1) A thickness prediction device for a surface modified layer of a workpiece formed using a laser, comprising: a laser irradiation condition acquisition unit that acquires laser irradiation conditions including at least a processing speed and a laser output condition for each position on the surface of the workpiece, a material information acquisition unit that acquires material information of the workpiece, and a surface modified layer thickness prediction unit that predicts the thickness of the surface modified layer at each position on the workpiece based on the laser irradiation conditions and the material information.

[0054] (Supplementary Note 2) The thickness prediction device according to Supplementary Note 1, further comprising a display unit that displays the thickness of the surface modification layer.

[0055] (Supplementary Note 3) A thickness prediction device according to Supplementary Note 1, comprising: a machining simulation execution unit that creates point sequence data including at least coordinate values, feed rates, and laser output conditions on a machining path based on CNC data including at least parameter settings and a machining program; and a workpiece setting information acquisition unit that acquires workpiece setting information including at least the shape of the workpiece and the relative position of the workpiece and the machining path, wherein the laser irradiation condition acquisition unit calculates the laser irradiation conditions on the surface of the workpiece based on at least the point sequence data and the workpiece setting information.

[0056] (Supplementary Note 4) A thickness prediction device according to Supplementary Note 1, comprising: an operation data acquisition unit that acquires operation data obtained during processing, the operation data including at least coordinate values, feed rate, and laser output conditions; and a workpiece placement information acquisition unit that acquires workpiece placement information including at least the shape of the workpiece and the relative position of the workpiece and the processing path, wherein the laser irradiation condition acquisition unit calculates the laser irradiation conditions on the surface of the workpiece based on at least the operation data and the workpiece placement information.

[0057] (Supplementary Note 5) The thickness prediction device according to Supplementary Note 2, further comprising a designated position identification unit that identifies a position on the surface of the workpiece, and the display unit displays the thickness of the surface modification layer at the identified position.

[0058] (Supplementary Note 6) The thickness prediction device according to Supplementary Note 3, wherein the machining simulation execution unit creates point sequence data including at least coordinate values ​​on the machining path, laser output conditions, feed speeds, and additional material supply conditions.

[0059] (Supplementary Note 7) The thickness prediction device according to any one of Supplementary Notes 1 to 6, which displays the thickness of the surface modification layer numerically.

[0060] (Supplementary Note 8) The thickness prediction device according to any one of Supplementary Notes 1 to 6, wherein the degree of thickness of the surface modification layer is displayed by changing the display mode of the workpiece.

[0061] (Appendix 9) A method for predicting the thickness of a surface modification layer formed using a laser, in which a computer as a device for predicting the thickness of a surface modification layer of a workpiece performs the following processes: acquires laser irradiation conditions including at least a processing speed and a laser output condition for each position on the surface of the workpiece; acquires material information of the workpiece; and predicts the thickness of the surface modification layer at each position on the workpiece based on the laser irradiation conditions and the material information.

[0062] 10, 10A, 10B, 10C Thickness prediction device 11 Laser irradiation condition acquisition unit 12 Material information acquisition unit 13 Surface modification layer thickness prediction unit 14 Display unit 15 CNC data storage unit 16 Machining simulation execution unit 17 Workpiece placement information acquisition unit 18 Operation data acquisition unit 19 Designated position identification unit

Claims

1. A thickness prediction device for a surface modification layer of a workpiece formed using a laser, comprising: A laser irradiation condition acquisition unit that acquires laser irradiation conditions including at least the processing speed and laser output conditions at each position on the surface of the workpiece; A material information acquisition unit that acquires material information of the workpiece; A surface modification layer thickness prediction unit that predicts the thickness of the surface modification layer at each position of the workpiece based on the laser irradiation conditions and the material information. A thickness prediction device equipped with the above components.

2. The thickness prediction device according to claim 1, further comprising a display unit that displays the thickness of the surface modification layer.

3. A machining simulation execution unit that creates point sequence data including at least coordinate values, feed rates, and laser output conditions on a machining path based on at least CNC data including parameter settings and machining programs; A workpiece installation information acquisition unit that acquires workpiece installation information including at least the shape of the workpiece and the relative position between the workpiece and the machining path. The laser irradiation condition acquisition unit calculates the laser irradiation conditions on the surface of the workpiece based on at least the point sequence data and the workpiece installation information. The thickness prediction device according to claim 1.

4. An operation data acquisition unit that acquires operation data including at least coordinate values, feed rates, and laser output conditions obtained during machining; A workpiece installation information acquisition unit that acquires workpiece installation information including at least the shape of the workpiece and the relative position between the workpiece and the machining path. The laser irradiation condition acquisition unit calculates the laser irradiation conditions on the surface of the workpiece based on at least the operation data and the workpiece installation information. The thickness prediction device according to claim 1.

5. The thickness prediction device according to claim 2, further comprising a designated position identification unit that identifies a position on the surface of the workpiece, The display unit displays the thickness of the surface modification layer at the identified position.

6. The thickness prediction device according to claim 3, wherein the machining simulation execution unit creates point sequence data including at least coordinate values, laser output conditions, feed rates, and additional material supply conditions on the machining path.

7. The thickness prediction device according to any one of claims 1 to 6, wherein the thickness of the surface modification layer is numerically displayed.

8. The thickness prediction device according to any one of claims 1 to 6, wherein the degree of the thickness of the surface modification layer is displayed by a change in the display mode of the workpiece.

9. A computer as a thickness prediction device for a surface modification layer of a workpiece formed using a laser performs at least a process of acquiring laser irradiation conditions including a processing speed and laser output conditions at each position on the surface of the workpiece, a process of acquiring material information of the workpiece, and a process of predicting the thickness of the surface modification layer at each position of the workpiece based on the laser irradiation conditions and the material information. A method for predicting the thickness of a surface modification layer.