Machined surface quality simulation device and machined surface quality display method

Abstract

A machined surface quality simulation device (1a) is a machined surface quality simulation device for simulating the appearance characteristics of a machined surface in a workpiece machined by a machined surface that drives an axis according to a machining program. The machined surface quality simulation device (1a) comprises: a machining error generation determination unit (11a) that determines whether a machining error that gives a characteristic to the appearance and a pre-set machining error has occurred based on data related to the movement of the axis, i.e., axis data; a machined surface shape calculation unit (12a) that calculates the machining error shape generated by the machining error based on the machining conditions and the position of the axis when the machined surface processes the workpiece; and a drawing unit (13a) that draws the calculated machining error shape.

Description

Technical Field

[0001] The invention relates to a processing surface quality simulation device and a processing surface quality display method for simulating the appearance characteristics of the processing surface in a workpiece. Background Art

[0002] A machine tool is a mechanical device that drives an axis according to a processing program to process a product of a desired shape. As a technology for achieving high-precision processing, the following technologies are known, namely, a technology that predicts the occurrence of processing errors before processing using simulation, or a technology that monitors the data output by the machine tool during processing to detect the occurrence of processing errors.

[0003] Patent document 1 discloses a 3D shape simulation, which calculates the volume of the portion removed from the workpiece by the tool according to the trajectory of the tool in each calculation step, and predicts the shape after processing. By using the technology of patent document 1, when the trajectory of the tool is known, the accurate processing shape can be predicted.

[0004] Patent Document 1: Japanese Patent Application Publication No. 2010-237843 Summary of the invention

[0005] However, according to the prior art involved in the above-mentioned patent document 1, there are the following problems, that is, in order to achieve high-precision simulation of three-dimensional shapes, a large amount of computing resources are required, and the prediction of the shape after processing takes time. In addition, in the technology of the above-mentioned patent document 1, the shape after processing can be accurately predicted, but on the other hand, the outer shape of the appearance is not simulated, so when a scratch of several microns is generated, the change of the outer shape of the surface cannot be confirmed.

[0006] The present invention has been proposed in view of the above-mentioned situation, and its object is to obtain a machined surface quality simulation device that can predict the appearance characteristics of the machined surface through simple calculations.

[0007] In order to solve the above-mentioned problems and achieve the purpose, the processing surface quality simulation device involved in the present invention simulates the appearance characteristics of the processing surface in the workpiece processed by the working machine that drives the axis according to the processing program. The processing surface quality simulation device involved in the present invention has: a processing error generation judgment unit, which judges whether a processing error that gives characteristics to the appearance and a pre-set processing error occurs based on data related to the movement of the axis, that is, axis data; a processing surface shape calculation unit, which calculates the processing error shape generated by the processing error based on the processing conditions when the working machine processes the workpiece and the position of the axis; and a drawing unit, which draws the calculated processing error shape.

[0008] Effects of the Invention

[0009] The machined surface quality simulation device according to the present invention has the effect of being able to predict the appearance characteristics of a machined surface through simple calculations. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 It is a diagram showing a configuration example of a numerically controlled machine tool according to the first embodiment.

[0011] Figure 2 This is a schematic diagram for explaining the structure of the X-axis drive unit constituting the numerically controlled machine tool according to the first embodiment.

[0012] Figure 3 This is a diagram for explaining an example of the mechanism of the processing error in the first embodiment.

[0013] Figure 4 This is a diagram for explaining an example of the form of processing errors in the first embodiment.

[0014] Figure 5 This is a block diagram showing the structure of the machined surface quality simulation device according to the first embodiment.

[0015] Figure 6 This is a flowchart showing the procedure of the machined surface quality simulation performed by the machined surface quality simulation device according to the first embodiment.

[0016] Figure 7 This is a diagram showing a first example of a processing path in the first embodiment.

[0017] Figure 8 This is a diagram showing an example of a waveform of acceleration during machining in the first embodiment.

[0018] Fig. 9 This is a diagram showing a first example of an image generated by the machined surface quality simulation device according to the first embodiment.

[0019] Fig.10 This is a diagram showing an example of an error locus drawn by the machined surface quality simulation device according to the first embodiment.

[0020] Fig.11 This is a diagram showing an example of a tool and a machining error shape in the first embodiment.

[0021] Fig.12 This is a diagram for explaining a variation of the mechanical structure for floating the cutter in the first embodiment.

[0022] Fig.13This is a diagram showing an example of an acceleration waveform when precision machining is performed in the first embodiment.

[0023] Fig.14 This is a diagram showing a second example of an image generated by the machined surface quality simulation device according to the first embodiment.

[0024] Fig.15 This is a diagram showing a second example of the processing path in the first embodiment.

[0025] Fig.16 This is a diagram showing a third example of an image generated by the machined surface quality simulation device according to the first embodiment.

[0026] Fig.17 This is a diagram showing a configuration example of a control circuit according to the first embodiment.

[0027] Fig.18 This is a diagram showing a configuration example of a dedicated hardware circuit according to the first embodiment.

[0028] Fig.19 This is a block diagram showing the structure of a machined surface quality simulation device according to the second embodiment.

[0029] Fig. 20 This is a flowchart showing the procedure of the machined surface quality simulation performed by the machined surface quality simulation device according to the second embodiment.

[0030] Fig.21 This is a diagram showing an example of an image generated by the machined surface quality simulation device according to the second embodiment.

[0031] Fig. 22 This is a block diagram showing the structure of a machined surface quality simulation device according to the third embodiment.

[0032] Fig.23 This is a flowchart showing the procedure of the machined surface quality simulation performed by the machined surface quality simulation device according to the third embodiment.

[0033] Fig.24 This is a diagram showing an example of an image generated by the machined surface quality simulation device according to the third embodiment.

[0034] Fig.25 This is a diagram for explaining the vibration of the tool predicted in the fourth embodiment.

[0035] Fig.26 This is a diagram showing an example of an image generated by the machined surface quality simulation device involved in the fourth embodiment.

[0036] Fig. 27This is a block diagram showing the structure of a machined surface quality simulation device according to the fifth embodiment.

[0037] Fig.28 This is a diagram showing an example of an image generated by the machined surface quality simulation device involved in the fifth embodiment.

[0038] Fig.29 This is a block diagram showing the structure of a machined surface quality simulation device according to a sixth embodiment.

[0039] Fig.30 This is a block diagram showing a configuration example of a machine learning device included in the machined surface quality simulation device according to the sixth embodiment. DETAILED DESCRIPTION

[0040] Hereinafter, a machined surface quality simulation device and a machined surface quality display method according to an embodiment will be described in detail with reference to the drawings.

[0041] Implementation method 1.

[0042] Figure 1 1 is a diagram showing a configuration example of a numerically controlled machine tool 99 according to Embodiment 1. The numerically controlled machine tool 99 is a machine tool that drives axes according to a machining program. In Embodiment 1, the numerically controlled machine tool 99 is a vertical cutting machine having three orthogonal axes.

[0043] The numerical control machine tool 99 has an X-axis drive unit 93X that drives the X-axis, a V-axis drive unit 93V that drives the V-axis, a Y-axis drive unit 93Y that drives the Y-axis, a Z-axis drive unit 93Z that drives the Z-axis, and a spindle 83. The numerical control machine tool 99 is a machine tool driven in series, and has a structure called a gantry structure. The X-axis drive unit 93X and the V-axis drive unit 93V drive the Y-axis drive unit 93Y in the X direction. The Y-axis drive unit 93Y drives the Z-axis drive unit 93Z in the Y direction. The Z-axis drive unit 93Z drives the spindle 83 in the Z direction. The spindle 83 rotates the tool 76. The workpiece 78 as the processing object is set on the workbench 77. The numerical control machine tool 99 rotates the tool 76 while moving the spindle 83 via the X-axis drive unit 93X, the V-axis drive unit 93V, the Y-axis drive unit 93Y, and the Z-axis drive unit 93Z, thereby processing the workpiece 78 .

[0044] The operation performed by the numerical control machine tool 99 drives each axis according to the processing program, and realizes the processing shape of the workpiece 78 through cutting processing. Whether the operation of the numerical control machine tool 99 is normal or not is determined based on whether the processing shape of the workpiece 78 reaches a predetermined benchmark, specifically, whether the shape accuracy and surface accuracy as designed in advance are achieved.

[0045] In the numerical control machine tool 99, in each axis, the rotational motion of the motor 71 as an actuator is converted into a linear motion in the driving direction of each axis by the feed screw 73. At this time, the rotational motion is supported by the guide mechanism 72, so the axis has a degree of freedom only in the feed direction of the feed screw 73. As a result, in the numerical control machine tool 99, by combining the linear motion of each axis, the movement of the tool 76 in the three-dimensional space of XYZ, that is, the movement of the tool 76 with three degrees of freedom is realized. The numerical control machine tool 99 uses the spindle 83 to rotate the tool 76, and removes the material of the part that interferes with the tool 76 in the workpiece 78, thereby creating a three-dimensional processing shape of the workpiece 78.

[0046] Next, the X-axis drive unit 93X, the V-axis drive unit 93V, the Y-axis drive unit 93Y, and the Z-axis drive unit 93Z constituting the numerical control machine tool 99 are described. Here, the X-axis drive unit 93X is described as an example, but the contents described about the X-axis drive unit 93X are also the same in each of the V-axis drive unit 93V, the Y-axis drive unit 93Y, and the Z-axis drive unit 93Z.

[0047] Figure 2 1 is a schematic diagram for explaining the structure of the X-axis drive unit 93X constituting the numerical control machine tool 99 according to the first embodiment. Figure 2 As shown, the numerical control machine tool 99 includes a command value calculation unit 9, a servo control unit 6a, and a mechanical device unit 96. The mechanical device unit 96 includes a drive mechanism 97 and a mechanical structure 98. The command value calculation unit 9, the servo control unit 6a, and the drive mechanism 97 constitute an X-axis drive unit 93X.

[0048] The driving mechanism 97 is responsible for converting the rotational motion of the motor 71 of the X-axis into a straight motion and supporting the structure for the conversion. In the X-axis driving unit 93X, the rotational motion of the motor 71 is transmitted to the feed screw 73 via the coupling 74, and is converted into a straight motion via the nut 80 and the reducer 79. The straight motion of the feed screw 73 is constrained by the support bearings 75a and 75b. Through the straight motion of the nut 80, the tool 76 is driven in the X direction together with the support body 90 that supports the X-axis. The support body 90 is a general term for the Z-axis and the structure for supporting it, which is sandwiched between the tool 76 and the nut 80. In addition, the range of the mechanical structure 98 varies according to the axis. For example, the driving mechanism 97 of the Z-axis does not have the function of converting the motion of the motor 71 of the X-axis when viewed from the X-axis, and is therefore included in the mechanical structure 98 of the X-axis.

[0049] The position instruction Xc of the X-axis is output from the instruction value calculation unit 9 and input to the servo control unit 6a. The position instruction Xc represents the position calculated by the instruction value calculation unit 9 according to the machining program, and represents the position of the driven body under the desired control state. The servo control unit 6a performs feedback control to reduce the error between the detected position Xd and the position instruction Xc, outputs the motor current Ix to the motor 71, and drives the drive mechanism 97. The detected position Xd is obtained by multiplying the rotation angle of the motor 71 detected by the rotation angle detector 2 installed on the motor 71 by the thread pitch of the feed thread 73. A mechanical structure 98 including the tool 76 as the control object is connected to the drive mechanism 97.

[0050] The servo control unit 6a controls the detected position Xd to match the position indicated by the position command Xc through feedback control. However, even if feedback control is performed, an error may occur between the tip position of the tool 76 and the processing point of the workpiece 78 during processing, and material cutting residue or overcutting may occur in the workpiece 78, thereby causing processing errors.

[0051] Figure 3 FIG. 1 is a diagram for explaining an example of the mechanism of the processing error in the first embodiment. Figure 3 FIG. 3 shows a processing error caused by the deformation of the support body 90 caused by the movement of the X-axis driving unit 93X, and a processing error that cannot be addressed by feedback control.

[0052] When the X-axis drive unit 93X is accelerating or decelerating, the driving force of the motor 71 is transmitted to the support body 90 via the feed screw 73. When the rigidity of the support body 90 is insufficient, the driving force of the motor 71 is transmitted to the support body 90, thereby deforming the support body 90. Due to this deformation, the tool 76 is displaced in the Z direction. The rotation angle detector 2 of the X-axis drive unit 93X can detect the error of the X-axis drive unit 93X generated in the X direction, but on the other hand, it cannot detect the error generated in the Z direction. In addition, since the deformation is generated on the outside of the Z-axis drive unit 93Z, it cannot be detected by the rotation angle detector 2 of the X-axis drive unit 93X.

[0053] As a result, the deformation of the support body 90 cannot be detected by any axis rotation angle detector 2, so feedback control does not work for the deformation. Due to the deformation of the support body 90, the tool 76 bites into the workpiece 78, resulting in a machining error. Since the tool 76 performs a rotational motion, when interfering with the workpiece 78, the material is removed from the surface of the workpiece 78 in a circular shape. Due to the machining error, a circular machining mark, i.e., a machining error shape, is generated.

[0054] Figure 4FIG. 1 is a diagram for explaining an example of the method of machining error in the first embodiment. Figure 4 , an example is shown in which the above deformation occurs when machining is performed at a constant speed while the axis moves in the X direction using a cylindrical tool 76 called a straight end mill. The movement direction 21 of the tool 76 is the X direction. Figure 4 In FIG. 1 , the shape of the machining error generated when the X-axis is decelerated near the center of the X-axis is schematically shown when viewed from the Z direction. Figure 4 , for reference, a change in the posture of the mechanical structure 98 when the axis is moved in the X direction is schematically shown.

[0055] exist Figure 4 In the example shown, the tool 76 decelerates near the center of the distance that the tool 76 moves in the direction of motion 21. Near the center, due to the change in the posture of the mechanical structure 98, the tool 76 sinks into the workpiece 78, thereby removing more than necessary material from the surface of the workpiece 78. Therefore, a circular processing mark with the same diameter as the outer shape of the tool 76 remains on the surface of the workpiece 78. As described above, a processing error shape that gives a feature to the appearance of the processing surface is generated on the processed surface of the workpiece 78. The processing error shape is set to be a shape generated on the processing surface due to the processing error. The processing error shape 20 illustrated in the first embodiment is a stamp mark shape generated when the tool 76 sinks into the workpiece 78 when the axis is accelerated or decelerated. Since the tool 76 rotates while advancing in the X direction, the processing error shape 20 is not a complete circle, but the processing error shape 20 is set to be a circle here.

[0056] In addition, Figure 3 and Figure 4In order to explain the mechanism of error generation in an easy-to-understand way, the posture change of the mechanical structure 98 is emphasized. The size of the posture change generated in actual processing is, for example, less than one hundred microns in a CNC machine tool 99 that processes metal, and less than a few microns in a high-precision CNC machine tool 99. It is difficult to visually confirm the posture change of the mechanical structure 98 at the moment when the error occurs. However, in the case of a metal processing surface, even if the processing error is a few microns, the processing error will be clearly felt by the human eye as a feature of the processing surface due to changes in the reflection and interference of light. Therefore, for example, even if the accuracy of the size is within the design tolerance, the quality of the processing surface observed by the human eye will be judged as insufficient, and sometimes regarded as processing failure. In the case of unqualified processing surface quality, rework of the processing and discarding of unqualified workpieces 78 occur, so it is not preferred. Examples of processing errors that characterize the appearance of the processed surface as described above include a stripe pattern caused by vibration of the mechanical structure 98 or a ribbed pattern caused by quadrant protrusions caused by friction.

[0057] Figure 5 1 is a block diagram showing the structure of a machined surface quality simulation device 1a according to Embodiment 1. The machined surface quality simulation device 1a performs a machined surface quality simulation to simulate the appearance characteristics of the machined surface of the workpiece 78 machined by the machine tool. The machined surface quality simulation device 1a simulates the appearance characteristics generated on the machined surface due to the machining error, that is, the machining error shape. The machined surface quality simulation device 1a performs the machined surface quality simulation to predict the machined surface quality.

[0058] The machined surface quality simulation device 1a includes a machining error occurrence determination unit 11a that determines whether a machining error has occurred, a machined surface shape calculation unit 12a that calculates a machining error shape, and a drawing unit 13a that draws the calculated machining error shape.

[0059] The machining error generation determination unit 11a inputs axis data related to each axis of the numerical control machine tool 99. The axis data is data related to the movement of the axis, and is a combination of one or more of position feedback, velocity feedback, acceleration feedback, position command, velocity command, and acceleration command, or all of them. The machining error generation determination unit 11a determines whether a preset error occurs as an error caused by the movement of the axis based on the axis data. The machining error generation determination unit 11a determines whether a machining error occurs for each machining error that characterizes the appearance of the machined surface. The machining error generation determination unit 11a outputs the position feedback and the determination result to the machined surface shape calculation unit 12a.

[0060] When it is determined that a machining error will occur, the machining surface shape calculation unit 12a calculates the machining error shape caused by the machining error and the position where the machining error shape occurs based on the position feedback of each axis and the machining condition information. The machining condition information is information on the machining conditions when the CNC machine tool 99 machines the workpiece 78.

[0061] The drawing unit 13a generates an image showing a state in which the machining error shape calculated by the machining surface shape calculation unit 12a is formed at the position calculated by the machining surface shape calculation unit 12a. The drawing unit 13a generates an image simulating the quality of the machined surface when the workpiece 78 is viewed from a designated line of sight. The drawing unit 13a outputs the generated image.

[0062] Next, the machined surface quality simulation performed by the machined surface quality simulation device 1 a will be described. Figure 6 This is a flowchart showing the procedure of the machined surface quality simulation performed by the machined surface quality simulation device 1 a according to the first embodiment.

[0063] In step S1, the machined surface quality simulation device 1a initializes the time data. Here, the machined surface quality simulation device 1a initializes the time t used for calculation. In step S2, the machined surface quality simulation device 1a updates the calculation step. Here, the machined surface quality simulation device 1a advances the time by dt equivalent to the calculation step, and sets t=t+dt. In embodiment 1, the calculation step is the time interval for calculation.

[0064] In step S3, the machined surface quality simulation device 1a obtains axis data. In the case of the numerically controlled machine tool 99, the machined surface quality simulation device 1a obtains six state quantities, namely, position feedback, velocity feedback, acceleration feedback, position command, velocity command, and acceleration command, for the X-axis, V-axis, Y-axis, Z-axis, and spindle 83, respectively.

[0065] In step S4, the machined surface quality simulation device 1a determines whether a preset machining error occurs. Here, the machining error occurrence determination unit 11a determines the occurrence of an error for each preset machining error that characterizes the appearance of the surface of the workpiece 78. For example, as errors that characterize the appearance, a machining error, i.e., an X-direction error, is set, which is a machining error caused by the tool 76 sinking relative to the surface of the workpiece 78 due to the deformation of the mechanical structure 98 in the X direction, and a machining error, i.e., a Y-direction error, is set. In this case, the machining error occurrence determination unit 11a determines whether an error occurs with respect to the X-direction error and the Y-direction error, respectively. The method for determining whether an error occurs will be described later.

[0066] When it is determined that none of the preset machining errors has occurred (step S4, No), the machined surface quality simulation device 1a returns the sequence to step S2. On the other hand, when it is determined that at least one of the preset machining errors has occurred (step S4, Yes), the machined surface quality simulation device 1a proceeds to step S5.

[0067] In step S5, the machined surface quality simulation device 1a calculates the machining error shape in the machined surface shape calculation unit 12a. The machined surface shape calculation unit 12a calculates the machining error shape based on the position feedback related to the axis at the time set in step S2. At this time, the machined surface shape calculation unit 12a calculates the machining error shape using the machining condition information. That is, the machined surface shape calculation unit 12a calculates the machining error shape caused by the machining error based on the machining condition information and the information representing the position of the axis, i.e., the position feedback. The calculation method of the machining error shape will be described later. The machined surface shape calculation unit 12a outputs the calculation result of the machining error shape to the drawing unit 13a. In addition, the machined surface shape calculation unit 12a calculates the position of the machining error shape and outputs the position information as the calculation result to the drawing unit 13a.

[0068] In step S6, the machined surface quality simulation device 1a calculates image data representing the appearance of the machining error shape. The drawing unit 13a draws the machining error shape calculated in step S5 by calculating the image data. The operator of the machined surface quality simulation device 1a calculates image data representing the appearance when the machined surface is observed from a desired angle. The angle representing the visual recognition direction is preset by inputting parameters or the like by the operator. Alternatively, the operator specifies the angle representing the visual recognition direction by operating the screen with a mouse or the like while observing the screen.

[0069] In step S7, the machined surface quality simulation device 1a determines whether the machining is completed. If the machining is not completed (step S7, No), the machined surface quality simulation device 1a returns the sequence to step S2. On the other hand, if the machining is completed (step S7, Yes), the machined surface quality simulation device 1a ends. Figure 6 The actions involved are in the order shown.

[0070] Next, a method for determining whether an error has occurred by the machining error occurrence determination unit 11 a will be described. Figure 7 FIG. 1 is a diagram showing a first example of a processing path in the first embodiment. Figure 7 In the figure, the machining path is represented by a dotted arrow. Figure 7, an example of a processing path in which the tool 76 processes one surface of the workpiece 78 is shown. In this processing, the tool 76 is not moved in the Z direction, but is moved in the XY plane. A straight end mill is used as the tool 76. The tool 76 starts to move from a processing start position P1 outside the workpiece 78, and processes the surface of the workpiece 78 while moving counterclockwise in the XY plane of the workpiece 78 along a spiral processing path from the outer periphery of the workpiece 78 toward the center of the workpiece 78. The tool 76 processes the surface of the workpiece 78 until it reaches a processing end position P2 near the center of the XY plane of the workpiece 78.

[0071] Figure 8 : is a diagram showing an example of the waveform of acceleration during machining in the first embodiment. Figure 8 The waveforms of the accelerations of the X-axis and Y-axis are shown in Figure 7 The waveform of acceleration when the tool 76 is moved in the machining path shown. However, the movement in the X direction is generated by the synchronous movement of the X-axis and the V-axis as the tandem axes. Generally speaking, the main axis and the driven axis in the tandem axes perform approximately the same movement, so whether or not an error is generated is determined based on the acceleration of the X-axis. However, the generation of an error may be determined in the V-axis independently of the X-axis, or the generation of a machining error may be determined based on the V-axis.

[0072] exist Figure 8 In the figure, the threshold value Th1, which is the criterion for judging the error caused by the deformation of the mechanical structure 98 in the X direction, and the threshold value Th2, which is the criterion for judging the error caused by the deformation of the mechanical structure 98 in the Y direction, are indicated by dotted lines. Each threshold value Th1 and Th2 is determined by a processing test performed in advance. The relationship between the acceleration of the X axis and the displacement in the Z direction is measured in advance, and the value of the acceleration judged as unqualified processing by the processing test can be used in the threshold value Th1. In the threshold values ​​Th1 and Th2, a common value can be used for each working machine, or different values ​​can be pre-set for each combination of the tool 76 or the workpiece 78. In the threshold values ​​Th1 and Th2, different values ​​can be set for each processing condition information such as the feed amount or feed speed per blade.

[0073] exist Figure 8 In the case of acceleration in the positive direction of the X-axis, there are five locations where errors are determined to occur because the acceleration exceeds the threshold value Th1. In contrast, there is no location where errors are determined to occur on the Y-axis. This is because the following characteristics exist, namely, Figure 1In the case of the numerically controlled machine tool 99 shown, since the spindle 83 is arranged in a protruding position in the X direction, it is easy to deform in the X direction. On the other hand, with respect to the Y direction, it is supported by two components, the X-axis and the V-axis, through the gantry structure, so it is not easy to deform.

[0074] In addition, in the above description, the algorithm used for determining the occurrence of an error is an example and can be changed appropriately. For example, the threshold value used as the criterion for determining the error can be set based on the difference between the speed command and the speed feedback, that is, the speed deviation. When the value representing the position exceeds the threshold value set for the position, and the acceleration exceeds the threshold value set for the acceleration, it can be determined that an error has occurred. Alternatively, the threshold value can be set based on the result after filtering the value of the acceleration. The determination formula for the occurrence of an error can be appropriately set according to the manner in which the error occurs in the mechanical structure 98.

[0075] Fig. 9 FIG. 1 is a diagram showing a first example of an image generated by the machined surface quality simulation device 1a according to the first embodiment. Fig. 9 2 shows an example in which a machining error shape 22 in a machining surface is depicted by arranging a circle having the same diameter as the diameter of the tool 76 at a position determined to have caused an error in the XY plane. The machining error generated in this example is a machining error characterized by the circular machining error shape 22. The machining error shape 22 is a stamp mark shape generated by the tool 76 sinking into the workpiece 78 when the axis is accelerated or decelerated, similarly to the machining error shape 20 described above.

[0076] The machining surface shape calculation unit 12a calculates a machining error shape 22 having a diameter equal to the diameter of the tool 76 in a manner that simulates the machining error at the location where the machining error occurs, in a range on the workpiece 78 that is determined to have a machining error. The machining error shape 22 describes a shape that simulates the machining error in a three-dimensional space. The drawing unit 13a calculates image data when the machining error shape 22 is observed from an arbitrary angle, thereby drawing an image of the state of the machining error shape 22 observed from an arbitrary angle. The drawing unit 13a outputs the drawn image. Fig. 9 In the example shown, the image drawn by the drawing unit 13 a is an image of the XY plane, that is, a two-dimensional image. Fig. 9 The two-dimensional image shown is an image when the workpiece 78 is observed from the positive direction in the Z direction. In addition, when generating an image of the state of the workpiece 78 observed from a direction inclined relative to the Z direction, for example, from a direction inclined 45 degrees relative to the Z direction, the drawing unit 13a performs a three-dimensional coordinate transformation to generate a two-dimensional image.

[0077] exist Fig. 9In the example shown, the machining error shape 22 is set to a simple circular shape in order to shorten the calculation time of the machining error shape 22. The machining surface shape calculation unit 12a can calculate the error trajectory of the tool used in the machining and when the machining error occurs as the machining error shape. In this case, the drawing unit 13a draws the error trajectory along the shape actually formed due to the machining error.

[0078] Fig.10 This is a diagram showing an example of an error locus drawn by the machined surface quality simulation device 1 a according to the first embodiment. Fig.10 The trajectory 24 shown is an example of an error trajectory drawn by the blade tip of a single-blade end mill, and is the trajectory of the blade tip when the end mill moves in the movement direction 21, i.e., the X direction, while the spindle 83 rotates three times in the rotation direction 23 while machining the workpiece 78. In this case, the trajectory 24 drawn by the blade tip is formulated as shown in the following formula (1).

[0079] [Formula 1]

[0080]

[0081] Among them, v x is the moving speed in the X direction, R is the radius of the tool 76, ω is the angular velocity of the spindle 83, and δ is the phase difference of the cutting edge position relative to the rotation angle of the spindle 83. In addition, in the case of a two-blade end mill, two trajectories with phases different by 180 degrees are superimposed to draw an error trajectory. As described above, the drawing unit 13a can calculate the motion trajectory of the cutting edge that is closer to the actual behavior and draw the error trajectory. As a result, the machined surface quality simulation device 1a can simulate a more accurate appearance of the machining error shape.

[0082] In the case of finishing where the quality of the machined surface is important, v is usually smaller than in the case of roughing. x Therefore, in the case of finish machining, the shape of the blade tip at the moment when the error occurs has no effect even if it is approximated by a circle. The machined surface quality simulation device 1a can calculate the machined surface shape in a short time by approximating the actual motion trajectory by a circular motion.

[0083] Furthermore, the machining error shape 22 that characterizes the appearance of the surface of the workpiece 78 differs for each tool 76 , and therefore it is necessary to calculate the machining error shape 22 that characterizes the appearance appropriately for each tool 76 . Fig.11 2 is a diagram showing an example of a tool 76 and a machining error shape 22 in the first embodiment. The radius end mill 25 and the ball end mill 26 are examples of the tool 76. Fig.112 shows a state where a radius end mill 25 is observed from the side, a machining error shape 22 formed by the radius end mill 25, a state where a ball end mill 26 is observed from the side, and a machining error shape 22 formed by the ball end mill 26. Fig.11 , a machining error shape 22 formed by a rounded end mill 25 is shown, and a portion of the root side of the blade tip in the rounded end mill 25 is indicated by a dotted line. In addition, a machining error shape 22 formed by a ball end mill 26 is shown, and a portion of the root side of the blade tip in the ball end mill 26 is indicated by a dotted line. Fig.11 The two machining error shapes 22 shown are examples of machining error shapes 22 that occur due to deformation of the mechanical structure 98 .

[0084] The rounded end mill 25 rounds the front end. The machining error shape 22 formed by the rounded end mill 25 is a circle smaller than the outer shape of the rounded end mill 25. Since the ball end mill 26 has one point at the front end in contact with the workpiece 78, the machining error shape 22 is one point. In addition, the machining error shape 22 can be obtained based on the distance to the blade tip position of the tool 76. The machining error shape 22 can be obtained by measuring the diameter of the shape actually transferred in a machining experiment or the like.

[0085] Next, an example of the quality of the machined surface when a different process from the above is predicted will be described. Here, an example of the case of precision machining will be described. In the case of precision machining, not only the sinking of the aforementioned tool 76 relative to the workpiece 78, but also the cutting residue generated by the floating of the tool 76 relative to the workpiece 78 may also cause machining errors that affect the quality of the machined surface.

[0086] Fig.12 FIG. 9 is a diagram for explaining a modification of the mechanical structure 98 for floating the cutter 76 in the first embodiment. Fig.12 FIG. 2 schematically shows a situation in which the support body 90 is deformed due to the movement of the X-axis driving unit 93X, and the tool 76 floats up compared to the surface of the workpiece 78. In such a state, the tool 76 floats up from the workpiece 78, and a cutting residue is generated in the workpiece 78. In such a case, the threshold value for determining the occurrence of a machining error is set for the absolute value of the acceleration of the axis.

[0087] Fig.13 : is a diagram showing an example of an acceleration waveform when precision machining is performed in the first embodiment. Fig.13 In the Figure 7 The following are examples of waveforms of accelerations in the X-axis and Y-axis when precision machining is performed in the same machining path as shown. Fig.132 shows a waveform representing the absolute value of the acceleration feedback of the axis. Fig.13 The dashed line shown indicates the threshold value for error generation. However, the threshold value may also be specified by an absolute value. As threshold values, a threshold value for the case where acceleration is generated in the positive direction and a threshold value for the case where acceleration is generated in the negative direction may be set separately in each axis. The determination of the occurrence of machining error may be implemented for each calculation step or only for the axis where acceleration is generated. The determination of the occurrence of machining error may be implemented within a preset time from the moment when acceleration is generated.

[0088] exist Fig.13 In the example shown, the absolute value of the acceleration feedback exceeds the threshold value at all the moments of acceleration and deceleration for each of the X-axis and the Y-axis. That is, machining errors occur at all the timings of acceleration and deceleration for each of the X-axis and the Y-axis. Fig.14 FIG. 2 is a diagram showing a second example of an image generated by the machined surface quality simulation device 1a according to the first embodiment. Fig.14 As shown in Fig.13 The following are examples of images that are drawn when machining errors occur in the X-axis and Y-axis, respectively.

[0089] The machining error shape 22 is calculated at the moment of acceleration and deceleration of the X axis and the moment of acceleration and deceleration of the Y axis, respectively. Fig.14 As shown in FIG. 1 , a double arc-shaped machining error shape 22 is calculated. Fig.14 The circular shape 27 shown by the middle dotted line indicates that the absolute value of the acceleration feedback exceeds the threshold value immediately after the machining starts. However, the machining error represented by the circular shape 27 is an error outside the workpiece 78, so the circular shape 27 is not calculated as the machining error shape 22 in the machining surface shape calculation unit 12a. The machining surface shape calculation unit 12a determines that the circular shape 27 is outside the workpiece 78 based on the information on the installation position of the workpiece 78 included in the machining condition information.

[0090] Next, an example of predicting the quality of the machined surface when the workpiece 78 is machined by a machining path different from the above will be described. Fig.15 FIG. 2 is a diagram showing a second example of a processing path in the first embodiment. Fig.15 In the figure, the machining path is indicated by the dotted arrows. Fig.15 The movement of the tool 76 on the XY plane in the machining path shown is Figure 7 The same is true for the machining paths shown. Fig.15 In the machining path shown, Figure 7 The difference of the processing path shown is that a processing end position P2 is set at a position away from the workpiece 78 in the Z direction. The processing end position P2 is set to be, for example, the origin of the machine. Fig.15In the case of the machining path shown, the numerically controlled machine tool 99 returns the tool 76 to the origin by lifting the tool 76 in the Z direction from the vicinity of the center of the XY plane in the workpiece 78 .

[0091] Fig.16 FIG. 3 is a diagram showing a third example of an image generated by the machined surface quality simulation device 1a according to the first embodiment. Fig.16 In the Fig.15 An example of an image drawn when the workpiece 78 is processed by the processing path shown. Fig.16 The circular shape 27 shown by the middle dotted line indicates that the absolute value of the acceleration feedback exceeds the threshold value after the tool 76 is lifted from the workpiece 78 in the Z direction. However, the machining error represented by the circular shape 27 is the machining error after the tool 76 is separated from the surface of the workpiece 78, so the circular shape 27 is not calculated as the machining error shape 22 in the machined surface shape calculation unit 12a.

[0092] According to the first embodiment, the machined surface quality simulation device 1a determines whether a machining error that gives a feature to the appearance and a pre-set machining error occurs based on the axis data, and calculates the machining error shape 22 generated by the machining error based on the machining condition information and the position of the axis. The machined surface quality simulation device 1a depicts the machining error shape 22 that can be recognized when the machined surface is visually viewed. Compared with the case where a high-precision simulation of a three-dimensional shape is required, the machined surface quality simulation device 1a can generate an image as a prediction result of the machined surface quality through simple calculation. As described above, the machined surface quality simulation device 1a has the effect of being able to predict the appearance feature of the machined surface through simple calculation.

[0093] Next, the hardware for realizing the machined surface quality simulation device 1a according to Embodiment 1 is described. The machining error occurrence determination unit 11a, the machined surface shape calculation unit 12a, and the drawing unit 13a are realized by a processing circuit. The processing circuit may be a circuit in which a processor executes software or a dedicated circuit.

[0094] In the case where the processing circuit is implemented by software, the processing circuit is, for example, Fig.17 The control circuit shown. Fig.172 is a diagram showing a configuration example of a control circuit 200 according to Embodiment 1. The control circuit 200 includes an input unit 201, a processor 202, a memory 203, and an output unit 204. The input unit 201 is an interface circuit for receiving data input from outside the control circuit 200 and giving the data to the processor 202. The output unit 204 is an interface circuit for sending data from the processor 202 or the memory 203 to the outside of the control circuit 200. In addition, the input unit 201 may include an input device for an operator to input information to the machined surface quality simulation device 1a. The output unit 204 may include a display device for displaying an image drawn by the drawing unit 13a.

[0095] In the processing circuit Fig.17 In the case of the control circuit 200 shown in FIG. 1 , the machining error generation determination unit 11a, the machined surface shape calculation unit 12a, and the drawing unit 13a are implemented by software, firmware, or a combination of software and firmware. The software or firmware is described as a program and stored in the memory 203. In the processing circuit, each function is realized by the processor 202 reading out the program stored in the memory 203 and executing it. That is, the processing circuit has a memory 203, which is used to store the program that the processing of the machined surface quality simulation device 1a is finally executed. In addition, these programs can be said to be the order and method for causing the computer to execute the machined surface quality simulation device 1a.

[0096] The processor 202 is a CPU (also called a Central Processing Unit, a central processing device, a processing device, an arithmetic device, a microprocessor, a microcomputer, a processor, or a DSP (Digital Signal Processor). The memory 203 is, for example, a nonvolatile or volatile semiconductor memory such as a RAM (Random Access Memory), a ROM (Read Only Memory), a flash memory, an EPROM (Erasable Programmable Read Only Memory), an EEPROM (registered trademark) (Electrically Erasable Programmable Read Only Memory), a magnetic disk, a floppy disk, an optical disk, a compact disk, a mini disk, or a DVD (Digital Versatile Disc).

[0097] Fig.17 This is an example of hardware in which each component is realized by a general-purpose processor 202 and a memory 203 , but each component may be realized by a dedicated hardware circuit. Fig.18 This is a diagram showing a configuration example of the dedicated hardware circuit 205 according to the first embodiment.

[0098] The dedicated hardware circuit 205 has an input unit 201, an output unit 204, and a processing circuit 206. The processing circuit 206 is a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a circuit combining them. Each function of the machined surface quality simulation device 1a can be implemented by the processing circuit 206 according to the functional category, or each function can be implemented by the processing circuit 206 in a centralized manner. In addition, each structural element can be implemented by combining the control circuit 200 and the hardware circuit 205.

[0099] The machined surface quality simulation device 1a can be connected to the CNC machine tool 99 via a network cable or a wireless network. Alternatively, the machined surface quality simulation device 1a can be physically installed on a remote server or cloud from the CNC machine tool 99 connected to the network.

[0100] Implementation method 2.

[0101] Fig.19 This is a block diagram showing the structure of a machined surface quality simulation device 1b according to Embodiment 2. In Embodiment 2, the same reference numerals are used for the same structural elements as those in Embodiment 1, and the structure different from that in Embodiment 1 is mainly described. The machined surface quality simulation device 1b has a machined surface shape calculation unit 12b that is different from the machined surface shape calculation unit 12a in Embodiment 1.

[0102] The machining error generation determination unit 11a outputs the determination result and the axis position information related to the generation of the machining error to the machined surface shape calculation unit 12b. The machined surface shape calculation unit 12b calculates the envelope curve based on the axis position information for the area determined as not generating the machining error. The envelope curve represents the trajectory of the outer shape of the tool 76 used for machining. The drawing unit 13a draws the calculated machining error shape and the calculated envelope curve.

[0103] Fig. 20 This is a flowchart showing the procedure of the machined surface quality simulation performed by the machined surface quality simulation device 1 b according to the second embodiment. Fig. 20 The sequence of steps S1 to S4 shown is the same as Figure 6 The same is true for the embodiment 1 shown.

[0104] When it is determined that a machining error will occur (step S4, Yes), the machined surface quality simulation device 1b calculates the machining error shape in step S5, similarly to the case of embodiment 1. On the other hand, when it is determined that no machining error will occur (step S4, No), the machined surface quality simulation device 1b proceeds to step S8.

[0105] In step S8, the machined surface quality simulation device 1b calculates the envelope in the machined surface shape calculation unit 12b. The envelope is a line shape generated by the blade tip of the tool 76 during machining, and is a machining error shape that simulates the machining error that affects the quality of the machined surface. The machining error shape as an envelope is generated due to the tiny steps between adjacent machining paths. Light is reflected and interfered in the steps, so that the machining error shape as an envelope may be recognized as a machining error when visually observed. Therefore, in embodiment 2, the machined surface quality simulation device 1b, like embodiment 1, calculates the envelope in an area where no machining error caused by the deformation of the mechanical structure 98 is generated, based on the calculation of the machining error shape caused by the deformation of the mechanical structure 98. If the machined surface quality simulation device 1b ends the sequence of step S8, the sequence proceeds to step S6.

[0106] The order of steps S5 to S7 is Figure 6 The same is true for the illustrated embodiment 1. The drawing unit 13 a generates an image including the shape and envelope of the machining error caused by the deformation of the mechanical structure 98 .

[0107] Fig.21 2 is a diagram showing an example of an image generated by the machined surface quality simulation device 1b according to the second embodiment. Fig.21 FIG. 2 shows an example of a circular machining error shape 22 and an envelope 30 being drawn. The envelope 30 is Figure 7 The case shown is similar to an example of an envelope curve when the tool 76 is moved.

[0108] According to the second embodiment, the machined surface quality simulation device 1b calculates the envelope, thereby generating an image including the shape and envelope of the machining error caused by the deformation of the mechanical structure 98. The machined surface quality simulation device 1b can simulate the machining error caused by the tiny step between adjacent machining paths as one of the elements of the machined surface quality.

[0109] Implementation method 3.

[0110] Fig. 22This is a block diagram showing the structure of a machined surface quality simulation device 1c according to Embodiment 3. In Embodiment 3, the same reference numerals are given to the same structural elements as those in Embodiment 1 or 2, and the description will be mainly about the structures different from those in Embodiment 1 or 2. The machined surface quality simulation device 1c includes a machined surface shape calculation unit 12c which is different from the machined surface shape calculation units 12a and 12b in Embodiment 1 or 2.

[0111] The machining error occurrence determination unit 11a outputs the determination result and the axis position information on the occurrence of the machining error to the machined surface shape calculation unit 12c. The machined surface shape calculation unit 12c calculates the envelope curve for the area determined as not having the machining error based on the axis position information. The drawing unit 13a draws the calculated machining error shape and the calculated envelope curve.

[0112] In the second embodiment, the machined surface quality simulation device 1b depicts the envelope of the entire trajectory of the blade tip of the tool 76. However, sometimes, depending on the machining conditions, the interval between adjacent portions in the machining path is shorter than the distance between the blade tips of the tool 76. In this case, one envelope that is processed first among the adjacent portions sometimes disappears because the other portions are processed. On the contrary, the portion that is processed first is cut deeper, so that sometimes the tool 76 does not contact the workpiece 78 when the tool 76 passes through the other portion. In this case, sometimes no envelope is generated in the other portion. Therefore, in the third embodiment, the machined surface shape calculation unit 12c deletes one of the adjacent envelopes, i.e., the region where the adjacent envelopes are calculated.

[0113] Fig.23 1 is a flowchart showing the procedure of the machined surface quality simulation performed by the machined surface quality simulation device 1c according to the third embodiment. Fig.23 In the order shown, Fig. 20 Step S9 is added to the same sequence of steps S1 to S8. In step S9, the machined surface shape calculation unit 12c deletes one of the adjacent envelopes in the region where the adjacent envelopes are calculated.

[0114] The machining surface shape calculation unit 12c obtains the order in which the tool 76 passes through each position on the machining path from the information of the machining path. The machining surface shape calculation unit 12c identifies the part that the tool 76 passes through first and the part that the tool 76 passes through later, with respect to the mutually adjacent parts in the machining path. Which of the adjacent envelope lines is deleted is set in advance based on the machining condition information. The remainder of the envelope line is sometimes determined by the inclination of the installed tool 76, so when the tool 76 is replaced, the setting related to the deletion of the adjacent envelope line can be changed. If the sequence of step S9 is ended, the machining surface quality simulation device 1c advances the sequence to step S6.

[0115] The order of steps S5 to S7 is Figure 6 The same is true for the illustrated embodiment 1. The drawing unit 13 a generates an image including the shape and envelope of the machining error caused by the deformation of the mechanical structure 98 .

[0116] In addition, the processing of deleting the calculated processing error shape by the processing surface shape calculation unit 12c can be applied not only to the envelope line, but also to the processing error shapes other than the envelope line. For example, the processing surface shape calculation unit 12c can delete one processing error shape with respect to the area where the processing error shapes generated by the deformation of the mechanical structure 98 overlap with each other. Alternatively, the processing surface shape calculation unit 12c can delete one of the processing error shape and the envelope line with respect to the area where the processing error shape generated by the deformation of the mechanical structure 98 overlaps with the envelope line.

[0117] Fig.24 2 is a diagram showing an example of an image generated by the machined surface quality simulation device 1c according to the third embodiment. Fig.24 FIG. 2 shows an example in which a circular machining error shape 22 and an envelope 30 are drawn. The envelope 30 and Figure 7 The illustrated case is also an example of an envelope curve when the tool 76 is moved.

[0118] Fig.24 The image shown is similar to Fig.21 The difference in the case shown is that one of the envelopes that overlap with each other is deleted, and one of the envelope and the machining error shape 22 that overlap with each other is deleted. Fig.24 In the image shown, among the overlapping envelopes, the envelope that the tool 76 passes through first is deleted. Fig.24 In the illustrated image, among the envelopes and machining error shapes 22 that overlap with each other, the envelope or machining error shape 22 that the tool 76 passes through first is deleted.

[0119] According to Embodiment 3, the machined surface quality simulation device 1c deletes one of the adjacent envelopes in the area where the adjacent envelopes are calculated, thereby preventing the envelope that disappears due to machining or the envelope that is not formed from being drawn. Thus, the machined surface quality simulation device 1c can simulate the machined surface quality more accurately.

[0120] Implementation method 4.

[0121] In the fourth embodiment, a case where a machined surface quality simulation is performed on a machining error other than a machining error caused by deformation of the mechanical structure 98 is described. The machined surface quality simulation device 1c involved in the fourth embodiment has the same structure as the case of the third embodiment. In the fourth embodiment, the same reference numerals are given to the same structural elements as those in the first to third embodiments, and mainly the structures different from the first to third embodiments are described. In the fourth embodiment, the machined surface quality simulation device 1c simulates a stripe pattern generated on the machined surface due to vibration of the mechanical structure 98.

[0122] The acceleration A of the tool 76 tcp (s) by converting the acceleration of the axis A mot (s) is formulated as the transfer function G(s) of the input. The transfer function G(s) is expressed by the following equation (2). Here, ζ represents the attenuation of vibration, ω represents the vibration frequency, K represents the amplitude ratio, and s represents the Laplace operator.

[0123] [Formula 2]

[0124]

[0125] Fig.25 This is a diagram for explaining the predicted vibration of the tool 76 in the fourth embodiment. Fig.25 The waveform shown represents the vibration of the tool 76 caused by the vibration of the mechanical structure 98 in the Y direction, and represents the vibration of the tool 76 in the Y direction. Fig.25 The vertical axis of the graph shown is the tool vibration estimated from the acceleration of the Y axis, and the horizontal axis is the time. Threshold Th3 is a threshold value used as a criterion for determining an error, and is set to be a threshold value of the acceleration of the tool 76. Fig.25 In FIG. 1 , the tool vibration when the acceleration is a threshold value Th3 is indicated by a dotted line. The threshold value Th3 is determined by a machining test performed in advance.

[0126] The machining error occurrence determination unit 11a receives the acceleration of the axis as input and determines the acceleration of the tool 76 based on the transfer function G(s). In the calculation step of the acceleration of the tool 76 exceeding the threshold value Th3, the vibration of the tool 76 generates a stripe pattern.

[0127] Fig.261 is a diagram showing an example of an image generated by the machined surface quality simulation device 1c according to the fourth embodiment. Fig.26 FIG. 2 shows an example of a circular machining error shape 22 formed by the vibration of the tool 76. Fig.26 As shown, a plurality of machining error shapes 22 are formed by overlapping each other in the Y direction.

[0128] In addition, the formula for determining the occurrence of vibration and the threshold value Th3 are examples and can be changed appropriately. In the formula for determining the occurrence of vibration, the acceleration A of the axis can be used instead of the above transfer function G(s). mot (s) The displacement Y of the tool 76 is used as input. tcp (s) is the transfer function G(s) formulated. mot (s) The displacement Y of the tool 76 is used as input. tcp The transfer function G(s) formulated as (s) is expressed by the following equation (3). The threshold value as the judgment standard of the error can be specified by the amplitude of the tool vibration. tcp (s) is the displacement caused by the vibration in the Y direction.

[0129] [Formula 3]

[0130]

[0131] In the fourth embodiment, the mechanical structure 98 is set to vibrate in the Y direction, but when the mechanical structure 98 vibrates in the X direction, or when the mechanical structure 98 vibrates in the X direction and the Y direction, the same is true as when the mechanical structure 98 vibrates in the Y direction. When the mechanical structure 98 vibrates in the X direction, the occurrence of the processing error is determined with respect to the X direction. When the mechanical structure 98 vibrates in the X direction and the Y direction, the occurrence of the processing error is determined with respect to each of the X direction and the Y direction.

[0132] According to the fourth embodiment, the machined surface quality simulation device 1 c can predict the machined surface quality by simple formulation.

[0133] The machining error shape is not limited to the stamp mark shape generated when the tool 76 sinks into the workpiece 78 when the axis accelerates or decelerates, or the stripe pattern shape generated when the tool 76 or the workpiece 78 vibrates when the axis accelerates or decelerates. The machining error shape may also be a flying white pattern generated when the tool 76 does not contact the workpiece 78, or a ripple pattern generated when the axis speed is discontinuous. The machined surface quality simulation device 1c can predict the appearance characteristics of the machining error shape that will affect the machined surface quality according to the mode of the machining error.

[0134] Implementation method 5.

[0135] Fig. 27 1 is a block diagram showing the structure of a machined surface quality simulation device 1d according to Embodiment 5. In Embodiment 5, the same reference numerals are given to the same structural elements as those in Embodiments 1 to 4, and the structure different from Embodiments 1 to 4 will be mainly described. The machined surface quality simulation device 1d includes a drawing unit 13b which is different from the drawing unit 13a in Embodiments 1 to 4. The drawing unit 13b performs a drawing process of superimposing a machining error shape on the surface of a three-dimensional shape model representing the shape of a workpiece 78 after machining.

[0136] In the fifth embodiment, the axis data from the simulator 100 is input to the machining error occurrence determination unit 11a instead of the numerical control machine tool 99. The simulator 100 is software that simulates the behavior of the numerical control machine tool 99. The simulator 100 uses a machining program to simulate the behavior of the numerical control machine tool 99 when the numerical control machine tool 99 performs machining. Specifically, the simulator 100 calculates a position command, a speed command, and an acceleration command according to the machining program. The simulator 100 predicts position feedback, speed feedback, and acceleration feedback according to the machining program.

[0137] The simulator 100 is software that simulates the functions of the numerical control device of the numerical control machine tool 99. The simulator 100 may be a transfer function or a formula that simulates the characteristics of each axis of the numerical control machine tool 99. The simulator 100 may be an artificial intelligence that takes a position command, a speed command, and an acceleration command as input and learns position feedback, speed feedback, and acceleration feedback.

[0138] The drawing unit 13b is input with 3D CAD (Computer Aided Design) information as 3D shape data and the processing error shape calculated by the processing surface shape calculation unit 12b. The 3D CAD information represents the shape of the workpiece 78 after processing. The drawing unit 13b draws a 3D shape model representing the shape of the workpiece 78 after processing based on the 3D CAD information. The drawing unit 13b draws a 3D shape model that simulates the outer shape of the workpiece 78 seen from a preset viewing angle, and superimposes the processing error shape related to the processing error that affects the processing surface quality on the surface of the 3D shape model. As described above, the drawing unit 13b performs a drawing process of superimposing the processing error shape on the surface of the 3D shape model that represents the shape of the workpiece 78 after processing.

[0139] Fig.28 2 is a diagram showing an example of an image generated by the machined surface quality simulation device 1d according to the fifth embodiment. Fig.282 shows an example of an image in which a machining error shape 22 is superimposed on a pyramid-shaped three-dimensional shape model representing a machined workpiece 78. A line graph simulating the appearance features of the machining error shape 22 is superimposed on a position where a machining error is determined to affect the machined surface quality.

[0140] According to the fifth embodiment, the machined surface quality simulation device 1d can predict the machined surface quality by using the result obtained by simulating the behavior of the numerically controlled machine tool 99 when it is connected to the simulator 100 instead of the numerically controlled machine tool 99. In addition, the machined surface quality simulation device 1d can predict the appearance characteristics of the machining error shape 22 in the machined workpiece 78 more easily by superimposing the machining error shape 22 on the three-dimensional shape model.

[0141] Implementation method 6.

[0142] Fig.29 1 is a block diagram showing the structure of a machined surface quality simulation device 1e according to Embodiment 6. In Embodiment 6, the same reference numerals are given to the same structural elements as those in Embodiments 1 to 5, and only the structures different from those in Embodiments 1 to 5 are described. The machined surface quality simulation device 1e is different from the machined surface quality simulation devices 1a, 1b, 1c, and 1d in Embodiments 1 to 5 in that it includes a machine learning device 110. In addition, the machined surface quality simulation device 1e includes a machining error generation determination unit 11b that is different from the machining error generation determination unit 11a in Embodiments 1 to 5.

[0143] A training data set including axis data and processing condition information is input to the machine learning device 110. Information on the location where the processing error occurs is input to the machine learning device 110. The processing condition information includes information such as the shape of the workpiece 78, the material of the workpiece 78, the tool diameter, the tool material, the tool shape, the number of blades, the feed rate per blade, the rotation speed of the tool 76, the mechanical structure information, the tool friction information, and the tool usage time. The mechanical structure information is information that characterizes the structure of the mechanical structure 98. A training data set that associates the acceleration and deceleration time constant, the command speed, and the processing condition information is constructed for each value of the axis position, speed, and acceleration at each position of the axis.

[0144] Fig.30This is a block diagram showing a structural example of a machine learning device 110 included in a machined surface quality simulation device 1e according to Embodiment 6. The machine learning device 110 includes a state observation unit 101 and a learning unit 102. The state observation unit 101 observes a training data set including axis data and machining condition information and information on a location where a machining error occurs as a state variable. The information on a location where a machining error occurs includes a judgment result of an actual machining error occurrence. That is, the state observation unit 101 observes axis data, machining condition information, and a judgment result of an actual machining error occurrence as a state variable. The learning unit 102 learns the relationship between a judgment value for determining whether a machining error occurs and machining conditions according to the training data set.

[0145] The learning algorithm used by the learning unit 102 may use any algorithm. As an example, the case where reinforcement learning is applied to the learning algorithm used by the learning unit 102 is described. Reinforcement learning is an intelligent agent, i.e., an acting subject, in a certain environment observes the current state and determines the action to be taken. The intelligent agent obtains rewards from the environment by selecting actions, and learns the countermeasures that obtain the most rewards after a series of actions. As representative methods of reinforcement learning, Q-learning and TD-learning are known. For example, in the case of Q-learning, the general update formula of the action value function Q(s, a), i.e., the action value table, is expressed by the following formula (4). The action value function Q(s, a) represents the value of the action of selecting action "a" based on the environment "s", i.e., the action value Q.

[0146] [Formula 4]

[0147] Q(s t , a t )←Q(s t , a t )+α(r t+1 +γmax a Q(s t+1 , a t )-Q(s t , a t ))…(4)

[0148] In the above formula (4), “s t+1 " represents the environment at time "t". t " represents the action at time "t". t ", the environment becomes "s t+1 ". t+1” represents the reward brought by the change of its environment. “γ” represents the discount rate. “α” represents the learning coefficient. When Q learning is applied, the judgment value of the processing error becomes the action “a t ”.

[0149] The update formula represented by the above formula (4) is that if the action value of the best action "a" at time "t+1" is greater than the action value Q of the action "a" executed at time "t", the action value Q is increased, and in the opposite case, the action value Q is decreased. In other words, the action value function Q (s, a) is updated in such a way that the action value Q of the action "a" at time "t" is close to the best action value at time "t+1". In this way, the best action value in a certain environment is successively propagated to the action value in its previous environment.

[0150] The learning unit 102 includes a reward calculation unit 103 and a function update unit 104. The reward calculation unit 103 calculates rewards based on state variables. The function update unit 104 updates a function for determining a determination value of a machining error according to the rewards calculated by the reward calculation unit 103.

[0151] Specifically, the reward calculation unit 103 calculates the reward "r" based on the judgment value of the processing error output from the processing error generation judgment unit 11b and the presence or absence of the processing error actually observed. For example, when the result of changing the processing conditions is that the judgment value of the processing error is consistent with the judgment result of the actual processing error generation, the reward calculation unit 103 increases the reward "r". The reward calculation unit 103 increases the reward "r" by assigning a value of "1" to the reward. In addition, the value of the reward is not limited to "1". In addition, when the result of changing the processing conditions is that the judgment value of the processing error is inconsistent with the judgment result of the actual processing error generation, the reward calculation unit 103 decreases the reward "r". The reward calculation unit 103 decreases the reward "r" by assigning a value of "-1" to the reward. In addition, the value of the reward is not limited to "-1".

[0152] The learning unit 102 obtains the actual result of determining the occurrence of a machining error from the information of the position where the machining error occurs. In addition, the actual result of determining the occurrence of a machining error may be a result obtained by a worker who determines the occurrence of a machining error by visually determining whether a machining error occurs. In the actual result of determining the occurrence of a machining error, information on the magnitude of the machining error extracted from the concave-convex information of the machined surface may be used. The concave-convex information of the machined surface is obtained by using an instrument such as a 3D coordinate measuring machine (CMM) or a microscope.

[0153] The function updating unit 104 updates the judgment model, i.e., the function, for determining the judgment value of the processing error according to the reward calculated by the reward calculating unit 103. The function updating can be performed by updating, for example, the action value table according to the training data set. The action value table is a data set that associates any action with its action value and stores it in the form of a table. For example, in the case of Q learning, the action value function Q(s ) represented by the above formula (4) is t , a t ) is used as a function for determining the judgment value of the processing error.

[0154] So far, the case where reinforcement learning is applied to the learning algorithm used by the learning unit 102 has been described, but learning other than reinforcement learning may also be applied to the learning algorithm. The learning unit 102 may perform machine learning using a well-known learning algorithm other than reinforcement learning, such as deep learning, neural network, genetic programming, inductive logic programming, or support vector machine.

[0155] The learning unit 102 can construct a training data set including information on all axes of the CNC working machine 99 and learn the judgment model for determining the judgment value of the processing error. It can also construct a training data set for each axis of the CNC working machine 99 and learn the judgment model for each axis for determining the judgment value of the processing error.

[0156] The learning unit 102 is not limited to being built into the machined surface quality simulation device 1e. The learning unit 102 may also be implemented by a device outside the machined surface quality simulation device 1e. In this case, the device that functions as the learning unit 102 may be a device that can be connected to the machined surface quality simulation device 1e via a network. The device that functions as the learning unit 102 may also be a device that exists on a cloud server. The machine learning device 110 may be connected to the machined surface quality simulation device 1e via a network. Fig.17 The same processor 202 and memory 203 or Fig.18 The same processing circuit 206 is used to implement the same processing circuit 206.

[0157] The machine learning device 110 outputs the judgment model, which is the learning result of the learning unit 102, to the machining error occurrence judgment unit 11b. The machining error occurrence judgment unit 11b calculates a judgment value based on the judgment model. The machining error occurrence judgment unit 11b determines whether a machining error that affects the quality of the machined surface has occurred based on the calculated judgment value.

[0158] According to embodiment 6, the machined surface quality simulation device 1e learns the relationship between the judgment value of the machining error and the machining conditions, thereby being able to accurately predict the occurrence of machining errors that will affect the machined surface quality when the conditions for generating machining errors that will affect the machined surface quality vary in a complex manner depending on the machining conditions.

[0159] The structures shown in the above embodiments illustrate an example of the content of the present invention. The structures of the embodiments can be combined with other known technologies. The structures of the embodiments can also be appropriately combined with each other. Part of the structure of the embodiments can be omitted or changed without departing from the scope of the gist of the present invention.

[0160] Description of the label

[0161] 1a, 1b, 1c, 1d, 1e machining surface quality simulation device, 2 rotation angle detector, 6a servo control unit, 9 command value calculation unit, 11a, 11b machining error generation determination unit, 12a, 12b, 12c machining surface shape calculation unit, 13a, 13b drawing unit, 20, 22 machining error shape, 21 movement direction, 23 rotation direction, 24 trajectory, 25 fillet end mill, 26 ball end mill, 27 circular shape, 30 envelope, 71 motor, 72 guide mechanism, 73 feed thread, 74 coupling, 75a, 75b support bearing, 76 tool, 77 worktable, 78 workpiece, 79 speed reducer, 80 nut, 83 spindle, 90 support body, 93V V-axis drive unit, 93X X-axis drive unit, 93Y Y-axis drive unit, 93Z Z-axis driving unit, 96 mechanical device unit, 97 driving mechanism, 98 mechanical structure, 99 CNC working machine, 100 simulator, 101 state observation unit, 102 learning unit, 103 feedback calculation unit, 104 function updating unit, 110 machine learning device, 200 control circuit, 201 input unit, 202 processor, 203 memory, 204 output unit, 205 hardware circuit, 206 processing circuit.

Claims

1. A machined surface quality simulation device for simulating the appearance characteristics of a machined surface of a workpiece machined by a machined tool that drives an axis according to a machining program, The machined surface quality simulation device is characterized by having: a machining error occurrence determination unit for determining whether a preset machining error has occurred as a machining error caused by the movement of the axis based on axis data which is data related to the movement of the axis; a machined surface shape calculation unit that, when it is determined that the machining error has occurred, calculates a machining error shape generated by the machining error based on machining conditions when the machine tool processes the workpiece and the position of the axis; and A drawing unit draws the calculated machining error shape.

2. The machined surface quality simulation device according to claim 1, characterized in that: The image drawn by the drawing unit is a two-dimensional image.

3. The machined surface quality simulation device according to claim 1, characterized in that: The drawing unit performs a drawing process of superimposing the machining error shape on a surface of a three-dimensional shape model representing the shape of the workpiece after machining.

4. The machined surface quality simulation device according to any one of claims 1 to 3, characterized in that: The machining error occurrence determination unit determines that the machining error will occur when the acceleration of the axis or the speed deviation of the axis exceeds a threshold value set in association with the axis and the machining error.

5. The machined surface quality simulation device according to any one of claims 1 to 3, characterized in that: have: a state observation unit that observes the axis data, the information on the machining conditions, and a determination result of actual machining error generation as a state variable; and a learning unit that learns the relationship between the determination value for determining whether the machining error occurs and the machining condition according to the data set created based on the state variable, The machining error occurrence determination unit determines whether the machining error has occurred based on the determination value calculated based on the learning result in the learning unit.

6. The machined surface quality simulation device according to any one of claims 1 to 3, characterized in that: The machined surface shape calculation unit calculates a trajectory of a tool used in machining and an error trajectory when the machining error occurs as the machining error shape.

7. The machined surface quality simulation device according to any one of claims 1 to 3, characterized in that: The processing error shape is a stamp mark shape produced when the tool used in processing sinks into the workpiece when the axis is accelerated or decelerated, a stripe pattern shape produced when the tool or the workpiece vibrates when the axis is accelerated or decelerated, a flying white pattern produced when the tool does not contact the workpiece, or a ripple pattern produced when the speed of the axis is discontinuous.

8. The machined surface quality simulation device according to any one of claims 1 to 3, characterized in that: The machined surface shape calculation unit calculates an envelope curve indicating a trajectory along which the outer shape of a tool used in machining passes, with respect to a region determined to have no machining error. The drawing unit draws the calculated machining error shape and the calculated envelope.

9. The machined surface quality simulation device according to claim 8, characterized in that: The machined surface shape calculation unit deletes one of the adjacent envelope lines, which are regions of the envelope lines adjacent to each other, for calculation.

10. A method for displaying the quality of a machined surface, the method comprising displaying an image simulating the appearance characteristics of a machined surface of a workpiece machined by the machined surface for a machined surface driving an axis according to a machining program, The method for displaying the quality of a processed surface is characterized by comprising the following steps: determining, based on axis data, which is data related to the movement of the axis, whether a predetermined machining error has occurred as a machining error caused by the movement of the axis; When it is determined that the machining error has occurred, calculating a machining error shape caused by the machining error based on machining conditions when the machine tool processes the workpiece and the position of the axis; and The calculated machining error shape is plotted.

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