Machining result evaluation device, machining result evaluation procedure, machining condition determination device and machining condition determination procedure

Abstract

A machining result evaluation device (1) for evaluating a machining result of a machining operation by a machine tool (4) comprises: a numerical control simulation unit (12) that simulates the operation of a numerical control device (2) that controls a servo control device (3) and issues a position command to a drive shaft of the machine tool; a servo control simulation unit (13) that simulates the operation of the servo control device based on the position command and issues a torque command to the drive shaft; a drive shaft simulation unit (14) that simulates the operation of the drive shaft based on the torque command; and a machining result evaluation unit (15) that evaluates a machining result based on information corresponding to the operation of the drive shaft.The drive shaft simulation unit outputs position information to the servo control simulation unit, indicating the position of the drive shaft, the servo control simulation unit performs feedback control of the drive shaft simulation unit using the position information, and the machining result evaluation unit evaluates a machining result obtained when the feedback control of the drive shaft simulation unit is simulated.

Description

Area

[0001] The present disclosure relates to a machining result evaluation apparatus, a machining result evaluation method, a machining condition determination apparatus, and a machining condition determination method for evaluating a machining result provided by a machine tool. background

[0002] In recent years, a machining simulation technique for a machining simulation device has been developed to evaluate the shape of a machined workpiece before a machine tool actually performs machining. This machining simulation device moves a tool in accordance with a machining program in a virtual space and removes a region through which the workpiece moves from a machining target or workpiece, thereby evaluating the shape of the machined workpiece. In fact, it is often impossible for a machine tool to perform machining in accordance with a machining program. For this reason, it is difficult for machining simulation based on the machining program to accurately evaluate the shape of a machined workpiece.

[0003] The machining simulation device described in Patent Literature 1 evaluates a shape of a machined workpiece by simulating an operation of a machine tool based on a position command output by a numerical control device and transmission characteristics of the machine tool. Citation listPatent literature

[0004] Patent Literature 1: Japanese Patent Application Laid-Open No. 2019-152936 Overview of the inventionProblem to be solved by the invention

[0005] Unfortunately, in the above-described technique of Patent Literature 1, machining is simulated without considering the response of the machine tool or a servo control device to the numerical control device. Therefore, the technique of Patent Literature 1 suffers from the inability to simulate the processing of a function based on the return value of a response from the servo control device or the machine tool to the numerical control device. As a result, the technique of Patent Literature 1 is unable to accurately evaluate a machining result.

[0006] The present disclosure has been made in view of the above, and an object thereof is to obtain a machining result evaluation apparatus that can accurately evaluate a machining result. Means to solve the problem

[0007] To solve the above problem and achieve the objective, the present disclosure provides a machining result evaluation device for evaluating a machining result of machining by a machine tool driven by a servo control device, the machining result evaluation device comprising: a numerical control simulation unit for simulating an operation of a numerical control device that controls the servo control device and outputting a position command to a drive shaft of the machine tool; a servo control simulation unit for simulating an operation of the servo control device based on the position command and outputting a torque command to the drive shaft; a drive shaft simulation unit for simulating an operation of the drive shaft based on the torque command;and a machining result evaluation unit for evaluating the machining result based on information corresponding to an operation of the drive shaft, wherein the drive shaft simulation unit outputs position information indicating a position of the drive shaft to the servo control simulation unit, wherein the servo control simulation unit simulates feedback control of the drive shaft simulation unit using the position information, and wherein the machining result evaluation unit evaluates the obtained machining result when the feedback control of the drive shaft simulation unit is simulated. Effects of the invention

[0008] The machining result evaluation device according to the present disclosure has an advantageous effect in that a machining result is accurately evaluated. Brief description of the drawings Fig. 1 is a block diagram showing a configuration of a machining result evaluation system including a machining result evaluation apparatus according to a first embodiment. Fig. 2 is a view for explaining an example of a process to be simulated by the machining result evaluation apparatus according to the first embodiment. Fig. 3 is a flowchart showing a machining procedure of a process to be executed by the machining result evaluation apparatus according to the first embodiment. Fig. 4 is a diagram showing an exemplary configuration of processing circuits when the processing circuits of the machining result evaluation apparatus according to the first embodiment are implemented by an arithmetic device and a memory. Fig. 5 is a diagram showing an example of processing circuits when the processing circuits of the machining result evaluation apparatus according to the first embodiment are configured by dedicated hardware. Fig. 6 is a block diagram showing a configuration of a machining condition determining device according to a second embodiment. Fig. 7 is a block diagram showing a configuration of a machining condition determination unit when the machining condition determination device according to the second embodiment calculates a machining condition corresponding to a machining result using an inference model. Fig. 8 is a block diagram showing a configuration of a machine learning apparatus according to the second embodiment. Fig. 9 is a diagram for explaining an example of a neural network used by the machine learning apparatus according to the second embodiment. Fig. 10 is a flowchart showing a machining procedure of a process to be executed by the machining condition determining device according to the second embodiment. Description of embodiments

[0009] A machining result evaluation apparatus, a machining result evaluation method, a machining condition determination apparatus, and a machining condition determination method according to embodiments of the present disclosure will be described in detail below with reference to the drawings. First embodiment.

[0010] Fig. 1 is a block diagram showing a configuration of a machining result evaluation system including a machining result evaluation device according to a first embodiment. A machining result evaluation system 101 includes a machining result evaluation device 1, a numerical control device 2, a servo control device 3, and a machine tool 4.

[0011] In the machining result evaluation system 101, the numerical control device 2 outputs a position command, and the servo control device 3 controls a drive shaft of the machine tool 4 to follow the position command, thereby performing cutting machining.

[0012] During cutting, the drive shaft of the machine tool 4 operates to move a tool attached to a spindle of the machine tool 4 and a workpiece (object to be machined) fixed to a table or a rotary spindle of the machine tool 4. During cutting, the spindle or the rotary spindle rotates to rotate the tool or the workpiece, and the tool comes into contact with the workpiece, so that the tool cuts off a part of the workpiece.

[0013] The numerical control device 2 analyzes a command code described in a machining program and outputs the position command based on the command code to the servo control device 3.

[0014] The servo control device 3 controls the drive shaft connected to the drive shaft via a motor of the machine tool 4 based on the position command received from the numerical control device 2. Furthermore, the servo control device 3 performs feedback control. Specifically, the servo control device 3 performs feedback control to reduce a deviation between a position of the drive shaft detected by a detector (not shown) and the position command received from the numerical control device 2, and determines a current to the motor to control the drive shaft.

[0015] The machining result evaluation device 1 is a computer that evaluates a machining result of the machining by the machine tool 4. An example of the machining performed by the machine tool 4 is cutting machining. The machining result evaluation device 1 includes a numerical control simulation unit 12, a servo control simulation unit 13, a drive shaft simulation unit 14, a machining result evaluation unit 15, and a display unit 16.

[0016] The numerical control simulation unit 12 simulates a process to be executed by the numerical control device 2. Specifically, the numerical control simulation unit 12 analyzes a command code described in the machining program and outputs a position command to the servo control simulation unit 13.

[0017] The servo control simulation unit 13 simulates a process to be executed by the servo control device 3. Specifically, the servo control simulation unit 13 performs feedback control to reduce a deviation between the position command obtained from the numerical control simulation unit 12 and the detected position obtained from the drive shaft simulation unit 14, and outputs a torque command to the drive shaft simulation unit 14.

[0018] The drive shaft simulation unit 14 simulates the operation of the drive shaft based on a drive shaft model that models the operation of the drive shaft of the machine tool 4. Specifically, the drive shaft simulation unit 14 simulates the motion of the drive shaft of the machine tool 4 based on the torque command received from the servo control simulation unit 13 and a response characteristic (e.g., a transfer function) for the torque command. Furthermore, the drive shaft simulation unit 14 calculates position information indicating the detected position of the drive shaft and outputs it to the servo control simulation unit 13. Since the tool is driven by the drive shaft, the position of the drive shaft corresponds to a position of the tool.

[0019] As described above, the numerical control simulation unit 12 calculates the position command and outputs it to the drive shaft of the machine tool 4 by simulating the operation of the numerical control device 2 controlling the servo control device 3. Furthermore, the servo control simulation unit 13 calculates the torque command and outputs it to the drive shaft by simulating the operation of the servo control device 3 based on the position command. Furthermore, the drive shaft simulation unit 14 simulates the operation of the drive shaft based on the torque command and calculates the position information of the drive shaft corresponding to the operation of the drive shaft. The drive shaft simulation unit 14 outputs the calculated position information to the servo control simulation unit 13 and the machining result evaluation unit 12.

[0020] The detector that detects a position of the drive shaft is a scale, and the drive shaft simulation unit 14 outputs position information about the drive shaft as it currently exists to the servo control simulation unit 13 and the machining result evaluation unit 15. Furthermore, the detector that detects a rotation angle of the motor is an encoder, and the drive shaft simulation unit 14 outputs the position information obtained by converting a position of the drive shaft into a rotation angle to the servo control simulation unit 13 and the machining result evaluation unit 15. For example, if the drive shaft is a feed screw mechanism, the drive shaft simulation unit 14 can obtain a rotation angle by dividing a position of the drive shaft by a lead of the feed screw.

[0021] The servo control simulation unit 13 simulates feedback control on the drive shaft simulation unit 14 using the position information from the drive shaft simulation unit 14. The servo control simulation unit 13 uses the position information obtained from the drive shaft simulation unit 14 to simulate the feedback control, and outputs the position information as a feedback position to the numerical control simulation unit 12.

[0022] The numerical control simulation unit 12 simulates the feedback control on the servo control simulation unit 13 using the position information from the servo control simulation unit 13. The numerical control simulation unit 12 thus simulates a process that operates based on the feedback position (position information) obtained from the servo control simulation unit 13.

[0023] Fig. 2 is a view for explaining an example of a process to be simulated by the machining result evaluation device according to the first embodiment. Here, it is described how the machine tool 4 moves the tool along a straight line 62 of a block n (n is an integer) and subsequently along a straight line 63 of a block (n+1), which is the next block. The two straight lines 62 and 63 are orthogonal to each other.

[0024] As in Fig. 2, the machine tool 4 moves the tool through a corner region 62 where the straight lines 62 and 63 intersect perpendicularly, in which case the movement in the next block (n+1) usually starts before the tool reaches the intersection point between the two straight lines 62 and 63 in this corner region 60 to allow the tool to rotate internally. Fig. 2 specifies a path 61 along which the tool rotates internally.

[0025] For the internal rotation of the tool, the numerical control device 2 may prevent the internal rotation by using an accurate stop function not to start the movement in the next block (n+1) until a "position check" is performed, that is, it is checked that a remaining distance in the previous block n before the start of the next block (n+1) is within a certain range.

[0026] The numerical control device 2 performs the position check based on the position information (feedback position) obtained from the servo control device 3. Therefore, the numerical control simulation unit 12 of the present embodiment simulates the precise stop function by obtaining the position information from the servo control simulation unit 13.

[0027] The numerical control simulation unit 12 can accurately evaluate the machining result (machining accuracy) at the corner portion 60 by simulating the position check. On the other hand, a machining result evaluation device that cannot simulate the position check cannot accurately evaluate the machining result of the corner portion 60.

[0028] Furthermore, since the numerical control simulation unit 12 simulates the position check, it is possible to simulate the path 61 that is the same as that in actual machining, making it possible to estimate the machining time that is the same as that in actual machining. The machining result evaluation device, which cannot simulate the position check, internally simulates the tool rotation more than in actual machining, so the machining result evaluation device estimates the machining time shorter than the actual machining.

[0029] Furthermore, the numerical control device 2 receives the spindle rotation angle and the position information of the rotary shaft from the servo control device 3, thereby providing a function called synchronous thread cutting, which performs thread cutting by synchronizing the rotation of the spindle and the feed of the drive shaft. In this regard, the numerical control simulation unit 12 receives the spindle rotation angle and the position information of the drive shaft from the servo control simulation unit 13, and simulates synchronous thread cutting based on the spindle rotation angle and the position information of the drive shaft. As a result, the numerical control simulation unit 12 can accurately evaluate whether a threaded hole has been accurately machined.However, since a machining result evaluation device that does not obtain the rotation angle of the spindle and the position information of the drive shaft cannot simulate synchronous thread cutting, it is not possible to accurately evaluate whether the threaded hole has been accurately machined.

[0030] As described above, the process of the numerical control simulation unit 12, which operates based on the position information obtained from the servo control simulation unit 13, can affect machining results such as machining accuracy and machining time. Therefore, to accurately evaluate the machining result, it is necessary to accurately simulate the process that occurs during actual machining, as the numerical control simulation unit 12 does.

[0031] The drive shaft simulation unit 14 simulates the operation of the drive shaft and outputs operation information indicating the operation of the drive shaft to the machining result evaluation unit 15. This operation information corresponds to the operation (movement path) of the tool. The operation information thus includes position information about the drive shaft.

[0032] The machining result evaluation unit 15 evaluates the machining result based on the operation information sent from the drive shaft simulation unit 14. The operation information sent from the drive shaft simulation unit 14 is operation information corresponding to a response from the servo control simulation unit 13 and a response from the drive shaft simulation unit 14. Thus, the operation information sent from the drive shaft simulation unit 14 is information reflecting the position information sent from the servo control simulation unit 13 to the numerical control simulation unit 12 and the position information sent from the drive shaft simulation unit 14 to the servo control simulation unit 13.The machining result evaluation unit 15 thus evaluates the machining result corresponding to the response of the servo control simulation unit 13 and the response of the drive shaft simulation unit 14.

[0033] As described above, the machining result evaluation unit 15 evaluates the machining result based on the operation information when simulating feedback control on the servo control simulation unit 13 and feedback control on the drive shaft simulation unit 14. Note that the machining result evaluation unit 15 may evaluate the machining result based on the information sent from the numerical control simulation unit 12 or the servo control simulation unit 13.

[0034] Note that the operation information sent from the drive shaft simulation unit 14 may be operation information corresponding to a response from the drive shaft simulation unit 14. Thus, the operation information sent from the drive shaft simulation unit 14 may be information that does not reflect the information sent from the servo control simulation unit 13 to the numerical control simulation unit 12. In this case, the machining result evaluation unit 15 evaluates the machining result in accordance with the response from the drive shaft simulation unit 14.

[0035] Note that the machining result evaluation unit 15 may evaluate the machining result based on data output from the numerical control simulation unit 12 to the servo control simulation unit 13 and / or data output from the servo control simulation unit 13 to the drive shaft simulation unit 14.

[0036] The machining result evaluated by the machining result evaluation unit 15 includes the machining time, the machining accuracy, the achieved surface quality and / or the energy consumption for machining by the machine tool 4. The energy consumption is the energy consumed when the tool is driven.

[0037] When evaluating the machining time, the machining result evaluation unit 15 can estimate the machining time based on at least the following data (response result): data (position command) output from the numerical control simulation unit 12; a response (detected position) from the servo control simulation unit 13; and a response (detected position) from the drive shaft simulation unit 14. The machining result evaluation unit 15 can estimate the machining time by calculating a sum of cycles (time durations) between the data on the position command or the detected position. The machining result evaluation unit 15 can thus estimate the machining time by multiplying the number of data points at positions specified by the position command or the detected position by one output cycle of the data.

[0038] When evaluating the machining accuracy and the achieved surface quality, the machining result evaluation unit 15 moves the tool in a virtual space along at least one piece of data (response result), such as: data (position command) output from the numerical control simulation unit 12; a response (detected position) from the servo control simulation unit 13; and a response (detected position) from the drive shaft simulation unit 14. The machining result evaluation unit 15 can estimate a shape of a machined workpiece after machining by executing the machining simulation by removing a region through which the tool moves from the workpiece. The machining result evaluation unit 15 thus calculates the shape of the machined workpiece by removing the region through which the workpiece moves from the region where the workpiece is located.

[0039] When calculating the energy consumption, the machining result evaluation unit 15 calculates a speed of the drive shaft based on at least one piece of data (response result), such as: data (position command) output from the numerical control simulation unit 12; a response (detected position) of the servo control simulation unit 13; and a response (detected position) of the drive shaft simulation unit 14. The machining result evaluation unit 15 can estimate the energy consumption of the motor by multiplying the torque command output from the servo control simulation unit 13 to the drive shaft simulation unit 14 by the speed of the drive shaft.

[0040] The machining result evaluation unit 15 sends the estimated machining result (machining time, machining accuracy, achieved surface quality and / or energy consumption) to the display unit 16. The display unit 16 displays the machining result evaluated by the machining result evaluation unit 15.

[0041] Fig. 3 is a flowchart showing a machining procedure of a process to be executed by the machining result evaluation device according to the first embodiment. The numerical control simulation unit 12 analyzes a command code described in the machining program, calculates a position command corresponding to the command code, and outputs the position command to the servo control simulation unit 13 (step S1).

[0042] The servo control simulation unit 13 simulates feedback control with a view to reducing a deviation between the position command obtained from the numerical control simulation unit 12 and the detected position obtained from the drive shaft simulation unit 14, and calculates a torque command corresponding to the feedback control and outputs the torque command to the drive shaft simulation unit 14 (step S2).

[0043] The drive shaft simulation unit 14 simulates a movement of the drive shaft based on the torque command received from the servo control simulation unit 13 and the response characteristic for the torque command, calculates position information indicating a position of the drive shaft as a detected position corresponding to the movement of the drive shaft, and outputs the position information to the servo control simulation unit 13 (step S3). Furthermore, the drive shaft simulation unit 14 outputs operation information corresponding to the position information of the drive shaft to the machining result evaluation unit 15.

[0044] The servo control simulation unit 13 calculates a feedback position (position information) corresponding to the detected position obtained from the drive shaft simulation unit 14 and outputs the feedback position to the numerical control simulation unit 12 (step S4).

[0045] The numerical control simulation unit 12 simulates a process to be executed by the numerical control device 2 based on the feedback position obtained from the servo control simulation unit 13 (step S5). In other words, the numerical control simulation unit 12 simulates a process that operates based on the feedback position obtained from the servo control simulation unit 13.

[0046] As described above, the machining result evaluation device 1 simulates feedback control based on the feedback position.

[0047] The machining result evaluation device 1 determines whether the machining is complete in the machining simulation (step S6). If the machining is not complete (step S6, No), the machining result evaluation device 1 returns to the processing of step S1 and repeats the simulation (processing of steps S1 to S6) until the machining is complete.

[0048] When the machining is completed (step S6, Yes), the machining result evaluation unit 15 evaluates the machining result based on the operation information sent from the drive shaft simulation unit 14 (step S7). In this case, the machining result evaluation unit 15 evaluates the machining result based on at least: data output from the numerical control simulation unit 12 to the servo control simulation unit 13; data output from the servo control simulation unit 13 to the drive shaft simulation unit 14; data (operation information) output from the drive shaft simulation unit 14 to the machining result evaluation unit 15; a response from the servo control simulation unit 13; and a response from the drive shaft simulation unit 14.

[0049] Note that the machining result evaluation device 1 can simulate machining, evaluating the machining result with the machining result evaluation unit 15. Thus, the machining result evaluation unit 15 can evaluate the machining result each time data is output from the numerical control simulation unit 12, the servo control simulation unit 13, or the drive shaft simulation unit 14. The machining result evaluation unit 15 sends the evaluated machining result to the display unit 16.

[0050] The display unit 16 displays the machining result evaluated by the machining result evaluation unit 15 (step S8). As a result, an operator can view the machining result. The operator changes settings (machining parameters, etc.) of the numerical control device 2 based on the machining result and operates the numerical control device 2 with the changed settings.

[0051] In the machining result evaluation device 1 according to the first embodiment, as described above, the drive shaft simulation unit 14 sends a response to the servo control simulation unit 13, thereby enabling the servo control simulation unit 13 to accurately simulate the process involved in actual machining. In the machining result evaluation device 1, the servo control simulation unit 13 further sends a response to the numerical control simulation unit 12, thereby enabling the numerical control simulation unit 12 to accurately simulate the process involved in actual machining. Therefore, the machining result evaluation device 1 according to the first embodiment can accurately evaluate the machining result.

[0052] A hardware configuration of the machining result evaluation device 1 will now be described. In the machining result evaluation device 1, the numerical control simulation unit 12, the servo control simulation unit 13, the drive shaft simulation unit 14, the machining result evaluation unit 15, and the display unit 16 are implemented by processing circuits. These processing circuits may be a memory and a processor that executes a program stored in the memory, or they may be dedicated hardware. The processing circuits are also referred to as control circuits.

[0053] Fig. 4 is a diagram showing an exemplary configuration of processing circuits when the processing circuits of the machining result evaluation apparatus according to the first embodiment are implemented by an arithmetic device and a memory. Fig. 4 shows a hardware configuration for implementing the machining result evaluation apparatus 1 according to the first embodiment.

[0054] The machining result evaluation device 1 includes an arithmetic device 41 which is a processor for executing arithmetic processing, a memory 42 used by the arithmetic device 41 as a work area, a storage device 43 which stores a program and data, a communication device 44 which communicates with the outside world, an input device 45 which receives an input from an operator, and a display device 46.

[0055] Examples of the arithmetic device 41 include a central processing unit (CPU), a processing device, a microprocessor, or a digital signal processor (DSP). An example of the memory 42 is a semiconductor memory. The storage device 43 is, for example, a non-volatile or volatile semiconductor memory such as a random access memory (RAM), a read-only memory (ROM), a flash memory, an erasable programmable read-only memory (EPROM), or an electrically erasable programmable read-only memory (EEPROM) (registered trademark), a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, a digital versatile disk (DVD), or the like.

[0056] A machining result evaluation program stored in the memory 43 is a program that causes the arithmetic device 41 to execute a procedure or method to be executed by the numerical control simulation unit 12, the servo control simulation unit 13, the drive shaft simulation unit 14, and the machining result evaluation unit 15. Thus, the arithmetic device 41 executes the machining result evaluation program stored in the memory device 43 by executing the machining result evaluation program.

[0057] Some functions of the display unit 16 are also implemented by the arithmetic device 41, which executes a display program stored in the storage device 43. The storage device 43 is also a device for storing the display program for implementing some functions of the display unit 16. The storage device 43 thus also stores a display program for causing the arithmetic device 41 to execute a part of the procedure or method to be executed by the display unit 16.

[0058] Examples of the input device 45 include a keyboard, a pointing device, and / or a mouse. The display device 46 is a means that implements the display unit 16. An example of the display device 46 is a liquid crystal display device. The input device 45 and the display device 46 may be integrated. In particular, the input device 45 and the display device 46 may be implemented by a touch screen.

[0059] Fig. 5 is a diagram showing an example of processing circuits when the processing circuits of the machining result evaluation apparatus according to the first embodiment are configured by dedicated hardware. Fig. 5 shows a processing circuit 51 when the numerical control simulation unit 12, the servo control simulation unit 13, the drive shaft simulation unit 14, the machining result evaluation unit 15 and / or the display unit 16 included in the machining result evaluation device 1 according to the first embodiment are implemented by the processing circuit.

[0060] Processing circuitry 51 is dedicated hardware. Processing circuitry 51 may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel-programmed processor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a combination of these.

[0061] Some of the functions of the numerical control simulation unit 12, the servo control simulation unit 13, the drive shaft simulation unit 14, the machining result evaluation unit 15, and the display unit 16 may be implemented by software or firmware, and the remaining functions may be implemented by dedicated hardware. As described above, the functions of the numerical control simulation unit 12, the servo control simulation unit 13, the drive shaft simulation unit 14, the machining result evaluation unit 15, and the display unit 16 may be implemented by hardware, software, firmware, or a combination thereof. Note that the servo control simulation unit 13, the drive shaft simulation unit 14, the machining result evaluation unit 15, and / or the display unit 16 may be implemented by separate processing circuits.

[0062] The machining result evaluation device 1 may be incorporated into the numerical control device 2, or it may be connected to the numerical control device 2 via a communication network. Alternatively, the machining result evaluation device 1 may be installed on a server or in a cloud.

[0063] As described above, in the machining result evaluation device 1 of the first embodiment, the drive shaft simulation unit 14 outputs the position information indicating the position of the drive shaft to the servo control simulation unit 13, and the servo control simulation unit 13 simulates the feedback control on the drive shaft simulation unit 14 using the position information. The machining result evaluation unit 15 then evaluates the machining result based on the operation information, etc., obtained when simulating the feedback control on the drive shaft simulation unit 14. As a result, the machining result evaluation device 1 can accurately simulate the process performed during actual machining, and thus can accurately evaluate machining results such as machining accuracy and machining time.

[0064] Furthermore, in the machining result evaluation device 1, the servo control simulation unit 13 outputs the position information to the numerical control simulation unit 12, and the numerical control simulation unit 12 simulates feedback control on the servo control simulation unit 13 using the position information. The machining result evaluation unit 15 evaluates the machining result based on the operation information, etc., obtained when simulating the feedback control on the servo control simulation unit 13 and the feedback control on the drive shaft simulation unit 14. As a result, the machining result evaluation device 1 can more accurately simulate the process performed during actual machining, and thus can more accurately evaluate machining results such as machining accuracy and machining time. Second embodiment.

[0065] Now, a second embodiment will be described with reference to the Fig. 6 to 9. In the second embodiment, a relationship between a machining result and a machining condition is learned in advance, and a machining condition corresponding to a machining result is determined.

[0066] Fig. 6 is a block diagram showing a configuration of a machining condition determining device according to the second embodiment. Among the individual components in Fig. 6, which achieve functions similar to those of the machining result evaluation device 1 of the Fig. 1 are denoted by the same reference numerals, and repetitive descriptions are omitted. A machining condition determination system 102 includes a machining condition determination device 5, the numerical control device 2, the servo control device 3, and the machine tool 4.

[0067] The machining condition determination device 5 according to the second embodiment includes the numerical control simulation unit 12, the servo control simulation unit 13, the drive shaft simulation unit 14, and the machining result evaluation unit 15, all of which are included in the machining result evaluation device 1 according to the first embodiment. The machining condition determination device 5 according to the second embodiment further omits the display unit 16 of the machining result evaluation device 1 according to the first embodiment. The machining condition determination device 5 according to the second embodiment includes a machine learning device 22 and a machining condition determination unit 21, both of which are omitted from the machining result evaluation device 1 according to the first embodiment.Thus, compared with the machining result evaluation device 1 according to the first embodiment, the machining condition determination device 5 includes the machine learning device 22 and the machining condition determination unit 21 instead of the display unit 16. Note that the machining condition determination device 5 may include the display unit 16.

[0068] In the second embodiment, differences from the first embodiment will be described. The machine learning device 22 receives a machining result output from the machining result evaluation unit 15. Furthermore, the machine learning device 22 receives a machining condition that the numerical control simulation unit 12 has used for simulation. By executing machine learning to calculate a relationship between the machining condition and the machining result, the machine learning device 22 generates an inference model (learned model). The machine learning device 22 sends the generated inference model to the machining condition determination unit 21.

[0069] The machining condition determination unit 21 calculates a suitable machining condition for a machining result input by the operator. The machining condition determination unit 21 calculates the machining condition corresponding to the machining result using the inference model generated by the machine learning device 22.

[0070] The machining condition determining unit 21 outputs machining parameters included in the determined machining condition to the numerical control device 2. Subsequently, the numerical control device 2 controls the servo control device 3 using the machining parameters sent from the machining condition determining unit 21.

[0071] Fig. 7 is a block diagram showing a configuration of a machining condition determination unit when the machining condition determination device according to the second embodiment calculates a machining condition corresponding to a machining result using the inference model. The machining condition determination unit 21 includes the inference unit 200. The inference unit 200 has an inference model learned by machine learning to output a machining condition upon receiving an input of a machining result from the machining result evaluation unit 15. When the machining result is input to the inference model learned in advance by machine learning to output the machining condition, the inference unit 200 outputs the machining condition corresponding to the machining result.

[0072] The machining condition corresponding to the machining result is a machining condition that reduces the difference between a desired machining result and a simulated machining result. Based on the simulated machining result, the machining condition determination unit 21 thus calculates a machining condition under which a desired machining result can be obtained.

[0073] Fig. Figure 8 is a block diagram showing a configuration of a machine learning device according to the second embodiment. The machine learning device 22 is a device that performs learning on an inference model and learns a relationship between a machining condition and a machining result. The machine learning device 22 includes a data acquisition unit 201 and a learning unit 202.

[0074] The data acquisition unit 201 acquires a combination of a machining condition and a machining result. Specifically, the data acquisition unit 201 acquires a combination of a machining condition and the machining time, machining accuracy, achieved surface quality, and / or energy consumption.

[0075] The data acquisition unit 201 acquires the machining condition from, for example, the numerical control simulation unit 12. Note that the data acquisition unit 201 may acquire the machining condition from the servo control simulation unit 13 or the drive shaft simulation unit 14. The data acquisition unit 201 also acquires, for example, a machining result corresponding to the machining condition from the machining result evaluation unit 15.

[0076] Note that the data acquisition unit 201 can acquire the machining condition from the numerical control device 2. The data acquisition unit 201 can further acquire a machining result of the workpiece actually machined by the machine tool 4. The data acquisition unit 201 outputs a combination of the machining condition and the machining result to the learning unit 202.

[0077] The learning unit 202 learns a relationship between a machining condition and a machining result according to a data set generated based on the combination of the machining condition and the machining result. Specifically, the learning unit 202 learns the relationship between the machining condition and the machining result using a data set generated based on a combination of the machining condition, machining time, machining accuracy, achieved surface quality, and energy consumption, all output from the data acquisition unit 201. The data set includes data in which a state variable and a machining condition are associated with each other. The state variable is one of the machining time, machining accuracy, achieved surface quality, and energy consumption.The learning unit 202 adapts the inference model so that the processing condition is output from the inference model when the state variable is input to the inference model. The learning unit 202 generates a learned inference model by learning a relationship between the processing condition and the processing result.

[0078] The machine learning device 22 generates a learned inference model to be used by the machining condition determination device 5. The machine learning device 22 is thus used to learn the machining condition learned by the machining condition determination device 5 and corresponding to the machining time, machining accuracy, achieved surface quality, and energy consumption. The machine learning device 22 may be a device separate from the machining condition determination device 5 or may be included in the machining condition determination device 5. If the machine learning device 22 is a device separate from the machining condition determination device 5, the machine learning device 22 is connected to the machining condition determination device 5, for example, via a communication network.The machine learning device 22 may further be located on a server or a cloud. The machining condition determination unit 21 may also be a separate device from the machining condition determination device 5, or it may be included in the machining condition determination device 5. If the machining condition determination unit 21 is a separate device from the machining condition determination device 5, the machining condition determination unit 21 is connected to the machining condition determination device 5 via, for example, a communication network. The machining condition determination unit 21 may further be located on a server or in a cloud.

[0079] For example, the learning unit 202 learns a relationship between a processing condition and a processing result through so-called supervised learning in accordance with a neural network model. Supervised learning refers to a model that provides a learning device with a large number of data sets for a specific input and a result ("label"), thereby learning features in the data sets and estimating a result from the input.

[0080] A neural network comprises an input layer consisting of a plurality of neurons, an intermediate layer (hidden layer) consisting of a plurality of neurons, and an output layer consisting of a plurality of neurons. The intermediate layer can comprise a single layer or two or more layers.

[0081] Fig. 9 is a diagram for explaining an example of a neural network used by the machine learning apparatus according to the second embodiment. In a Fig. In the three-layer neural network shown in Figure 9, for example, when a plurality of inputs are input to an input layer (X1 to X3), a value obtained by multiplying an input value by a weight W1 (w11 to w16) is input to an intermediate layer (Y1 and Y2). A value obtained by multiplying the value input to the intermediate layer (Y1 and Y2) by a weight W2 (w21 to w26) is output from an output layer (Z1 to Z3). The output result depends on the values ​​of the weight W1 and the weight W2.

[0082] For example, the neural network learns a relationship between a machining condition and a machining result through so-called supervised learning according to a data set generated based on a combination of the machining condition, machining time, machining accuracy, achieved surface quality, and energy consumption, all of which are acquired by the data acquisition unit 201. Thus, the neural network performs learning by adjusting the weight W1 and the weight W2 such that when the machining time, machining accuracy, achieved surface quality, and energy consumption are input to the input layer, the result output from the output layer approximates the machining condition.

[0083] The neural network can learn a relationship between a processing condition and a processing result through so-called unsupervised learning. Unsupervised learning is a technique in which a large amount of data from only input data is fed to the machine learning device 22, thereby learning the distribution of the input data to learn a device that performs, for example, compression, classification, and / or shaping in response to the input data without receiving the corresponding teacher output data. The neural network can, for example, cluster features in a dataset into similar features. The neural network uses the obtained result and assigns outputs that optimize the result with some criteria, thereby achieving output prediction.

[0084] There is what is known as semi-supervised learning, which represents an intermediate stage between unsupervised learning and supervised learning. Semi-supervised learning is learning with sets of input and output data and only input data.

[0085] The learning device 202 can learn a relationship between a machining condition and a machining result according to the data sets generated for a plurality of machining condition determining devices 5. The learning unit 202 can acquire data sets from a plurality of machining condition determining devices 5 used at one location, or it can learn a relationship between a machining condition and a machining result using data sets collected from a plurality of machining condition determining devices 5 operating independently at different locations.

[0086] The machining condition determination device 5 may be added at a point between targets from which data sets are to be collected, or the machining condition determination device 5 may be removed so that the machining condition determination device 5 is no longer the target. The machine learning device 22 that has learned the relationship between the machining condition and the machining result may be connected to another machining condition determination device 5 that is different from the device including the machine learning device 22, and may relearn and update the relationship between the machining condition and the machining result for this other machining condition determination device 5.

[0087] Deep learning can also be used as a learning algorithm for learning feature extraction in the learning unit 202. The learning unit 202 can perform machine learning in accordance with other known methods, such as genetic programming, functional logic programming, support vector machine, etc.

[0088] Fig. Fig. 10 is a flowchart showing a processing procedure of a process to be executed by the machining condition determining device according to the second embodiment. The machining condition determining device 5 executes a process similar to steps S1 to S7 described with reference to Fig. 3 described machining condition evaluation device 1.

[0089] In the machining condition determination device 5, the machining result evaluation unit 15 outputs the evaluated machining result to the machine learning device 22. The machine learning device 22 generates an inference model (inference unit 200) for calculating a relationship between a machining condition and a machining result (step S9). The machining condition determination unit 21 calculates a machining condition corresponding to the machining result using the inference model (step S10).

[0090] The machining condition determination unit 21 outputs machining parameters included in the determined machining condition to the numerical control device 2. As a result, the numerical control device 2 controls the servo control device 3 using the machining parameters sent from the machining condition determination unit 21.

[0091] As described above, the machining condition determination device 5 according to the second embodiment can accurately simulate the process operating in actual machining because the servo control simulation unit 13 sends a response to the numerical control simulation unit 12. Therefore, the machining condition determination device 5 according to the second embodiment can accurately evaluate the machining result.

[0092] Furthermore, using the inference model that learns a relationship between a machining condition and a precisely evaluated machining result, the machining condition determination device 5 according to the second embodiment calculates a machining condition corresponding to the machining result. The machining condition determination device 5 calculates a machining condition corresponding to a machining result determined by the operator.

[0093] When calculating the machining condition corresponding to the machining result determined by the operator, the machining condition determining device 5 can determine a machining condition that satisfies a machining result desired by the operator. Therefore, the machining condition determining device 5 according to the second embodiment can determine the machining condition that satisfies the machining result desired by the operator by only requiring the operator to input information indicating the desired machining result.

[0094] At least some of the functions of the machining condition determination unit 21 of the second embodiment may be implemented by an arithmetic device that executes a program stored in a storage device. The storage device is a storage device for storing a program that leads to the execution of at least some of the steps performed by the machining condition determination unit 21, and it is a storage device similar to the storage device 43. The arithmetic device in this case is an arithmetic device similar to the arithmetic device 41. At least some of the functions of the machining condition determination unit 21 may further be implemented by processing circuits. The processing circuits are processing circuits similar to those described with reference to Fig. 4 described processing circuits or those described with reference to Fig. 5 described processing circuits 51.

[0095] At least some of the functions of the inference unit 200 included in the machining condition determination unit 21 of the second embodiment may be implemented by an arithmetic device that executes a program stored in a storage device. The storage device is a storage device for storing a program that leads to the execution of at least some of the steps performed by the inference unit 200, and it is a storage device similar to the storage device 43. The arithmetic device in this case is an arithmetic device similar to the arithmetic device 41. At least some of the functions of the inference unit 200 may be implemented by processing circuits. The processing circuits are processing circuits similar to those described with reference to Fig. 4 described processing circuits, or the one described with reference to Fig. 5 described processing circuits 51.

[0096] At least some of the functions of the data acquisition unit 201 and the learning unit 202 included in the machine learning device 22 according to the second embodiment can be implemented by an arithmetic device that executes a program stored in a storage device. The storage device is a storage device for storing a program that leads to the execution of at least some of the steps performed by the data acquisition unit 201 and the learning unit 202, and it is a storage device similar to the storage device 43. The arithmetic device in this case is an arithmetic device similar to the arithmetic device 41. At least some of the functions of the data acquisition unit 201 and the learning unit 202 can be implemented by processing circuits. The processing circuits are processing circuits similar to those described with reference to Fig. 4 described processing circuits or those described with reference to Fig. 5 described processing circuits 51.

[0097] At least some of the functions of the machining condition determining device 5 can be further implemented by processing circuits similar to those described with reference to Fig. 4 described processing circuits or those described with reference to Fig. 5 described processing circuits 51 can be implemented.

[0098] As described above, in the machining condition determination device 5 of the second embodiment, the drive shaft simulation unit 14 outputs position information indicating a position of the drive shaft to the servo control simulation unit 13, and the servo control simulation unit 13 simulates feedback control on the drive shaft simulation unit 14 using the position information. The machining result evaluation unit 15 then evaluates a machining result based on the operation information when the feedback control is simulated on the drive shaft simulation unit 14. The machine learning device 22 generates an inference model for inferring a machining condition from the machining result, and the machining condition determination unit 21 determines the machining condition corresponding to the machining result using the inference model.As a result, the machining condition determining device 5 can determine a machining condition that corresponds to a machining result and that accurately simulates the process that occurs in actual machining.

[0099] In the machining condition determination device 5, the servo control simulation unit 13 further outputs the position information to the numerical control simulation unit 12, and the numerical control simulation unit 12 simulates feedback control on the servo control simulation unit 13 using the position information. Then, the machining result evaluation unit 15 evaluates the machining result based on operation information when simulating the feedback control on the servo control simulation unit 13 and the feedback control on the drive shaft simulation unit 14. As a result, the machining condition determination device 5 can more accurately simulate the process occurring during actual machining and can therefore more accurately determine the machining condition corresponding to the simulated machining result.

[0100] The configurations explained in the above embodiments show an example, and they can be combined with other known techniques, and it is also possible to combine embodiments with each other and omit and modify part of the configuration without departing from the subject matter of the present disclosure. List of reference symbols 1 machining result evaluation device; 2 numerical control device; 3 servo control device; 4 machine tool; 5 Machining condition determining device; 12 Numerical control simulation unit; 13 Servo control simulation unit; 14 Drive shaft simulation unit; 15 Processing result evaluation unit; 16 display unit; 21 Machining condition determination unit; 22 machine learning device; 41 arithmetic device; 42 storage; 43 storage device; 44 communication device; 45 input device; 46 display device; 51 processing circuits; 60 edge area; 61 path; 62, 63 straight line; 101 Processing result evaluation system; 102 Machining condition determination system; 200 inference unit; 201 data acquisition unit; 202 learning unit. QUOTES CONTAINED IN THE DESCRIPTION

[0000] This list of documents submitted by the applicant was generated automatically and is included solely for the convenience of the reader. This list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions. Cited patent literature

[0000] JP 2019-152936

[0004]

Claims

[1] Machining result evaluation device for evaluating a machining result of machining by a machine tool driven by a servo control device, wherein the machining result evaluation device comprises: a numerical control simulation unit for simulating an operation of a numerical control device that controls the servo control device and outputting a position command to a drive shaft of the machine tool; a servo control simulation unit for simulating an operation of the servo control device based on the position command and outputting a torque command to the drive shaft; a drive shaft simulation unit for simulating an operation of the drive shaft based on the torque command; and a machining result evaluation unit for evaluating the machining result based on information corresponding to an operation of the drive shaft, wherein the drive shaft simulation unit outputs position information indicating a position of the drive shaft to the servo control simulation unit, the servo control simulation unit simulates a feedback control of the drive shaft simulation unit using the position information, and the machining result evaluation unit evaluates the machining result obtained when the feedback control of the drive shaft simulation unit is simulated. [2] A machining result evaluation device according to claim 1, wherein the information corresponding to an operation of the drive shaft is the position information, and the machining result evaluation unit evaluates the machining result based on the position information. [3] A machining result evaluation device according to claim 1, wherein the servo control simulation unit outputs the position information to the numerical control simulation unit, the numerical control simulation unit simulates feedback control of the servo control simulation unit using the position information, and the machining result evaluation unit evaluates the machining result obtained when the feedback control of the servo control simulation unit and the feedback control of the drive shaft simulation unit are simulated. [4] A machining result evaluation device according to claim 3, wherein Information corresponding to an operation of the drive shaft is the position information output by the servo control simulation unit to the numerical control simulation unit, and the machining result evaluation unit evaluates the machining result based on the position information output by the servo control simulation unit to the numerical control simulation unit. [5] A machining result evaluation device according to claim 3, wherein Information corresponding to an operation of the drive shaft is the position command output by the numerical control simulation unit, and the machining result evaluation unit evaluates the machining result based on the position command output by the numerical control simulation unit. [6] A machining result evaluation device according to any one of claims 1 to 5, wherein the machining result evaluation unit evaluates a machining time, a machining accuracy, an achieved surface quality and / or an energy consumption of the machining by the machine tool. [7] Machining result evaluation method for evaluating a machining result of machining by a machine tool driven by a servo control device, The processing result evaluation procedure includes: a numerical control simulation step that simulates, by means of a numerical control simulation unit of a machining result evaluation device, an operation of a numerical control device that controls the servo control device and outputs a position command to a drive shaft of the machine tool; a servo control simulation step that simulates, by means of a servo control simulation unit of the machining result evaluation device, an operation of the servo control device based on the position command and outputs a torque command to the drive shaft; a drive shaft simulation step that simulates an operation of the drive shaft based on the torque command by means of a drive shaft simulation unit of the machining result evaluation device; and a machining result evaluation step that evaluates the machining result based on information corresponding to an operation of the drive shaft by means of a machining result evaluation unit of the machining result evaluation device, wherein the drive shaft simulation unit outputs position information indicating a position of the drive shaft to the servo control simulation unit in the drive shaft simulation step, the servo control simulation unit simulates a feedback control of the drive shaft simulation unit using the position information in the servo control simulation step, and the machining result evaluation unit evaluates, in the machining result evaluation step, the machining result obtained when the feedback control of the drive shaft simulation unit is simulated. [8] A processing result evaluation method according to claim 7, wherein the servo control simulation unit outputs the position information to the numerical control simulation unit in the servo control simulation step, the numerical control simulation unit simulates feedback control of the servo control simulation unit using the position information in the numerical control simulation step, and the machining result evaluation unit evaluates, in the machining result evaluation step, the machining result for the case where the feedback control of the servo control simulation unit and the feedback control of the drive shaft simulation unit are simulated. [9] Machining condition determining device for determining a machining condition when a machine tool driven by a servo control device performs machining, wherein the machining condition determining device comprises: a numerical control simulation unit for simulating an operation of a numerical control device that controls the servo control device and outputting a position command to a drive shaft of the machine tool; a servo control simulation unit for simulating an operation of the servo control device based on the position command and outputting a torque command to the drive shaft; a drive shaft simulation unit for simulating an operation of the drive shaft based on the torque command and outputting operation information indicative of an operation of the drive shaft; a machining result evaluation unit for evaluating a machining result of the machine tool based on information corresponding to an operation of the drive shaft; a machine learning device for generating an inference model for inferring the machining condition from the machining result; and a machining condition determination unit for determining a machining condition using the inference model, the machining condition corresponding to a machining result input by an operator, wherein the drive shaft simulation unit outputs position information indicating a position of the drive shaft to the servo control simulation unit, the servo control simulation unit simulates feedback control of the drive shaft simulation unit using the position information, and the machining result evaluation unit evaluates the machining result obtained when the feedback control of the drive shaft simulation unit is simulated. [10] Machining condition determining device according to claim 9, wherein the servo control simulation unit outputs the position information to the numerical control simulation unit, the numerical control simulation unit simulates feedback control of the servo control simulation unit using the position information, and the machining result evaluation unit evaluates the machining result obtained when the feedback control of the servo control simulation unit and the feedback control of the drive shaft simulation unit are simulated. [11] Machining condition determining method for determining a machining condition when a machine tool driven by a servo control device performs machining, wherein the machining condition determination method comprises: a numerical control simulation step that simulates, by means of a numerical control simulation unit of a machining condition determining device, an operation of a numerical control device that controls the servo control device and outputs a position command to a drive shaft of the machine tool; a servo control simulation step that simulates, by means of a servo control simulation unit of the machining condition determining device, an operation of the servo control device based on the position command and outputs a torque command to the drive shaft; a drive shaft simulation step that simulates, by means of a drive shaft simulation unit of the machining condition determining device, an operation of the drive shaft based on the torque command and outputs operation information indicating an operation of the drive shaft; a machining result evaluation step of evaluating, by a machining result evaluation unit of the machining condition determining device, a machining result of machining by the machine tool based on information corresponding to an operation of the drive shaft; a machine learning step that generates an inference model for inferring the machining condition from the machining result by means of a machine learning device; and a machining condition determination step that determines a machining condition using the inference model by means of a machining condition determination unit, the machining condition corresponding to a machining result input by an operator, wherein the drive shaft simulation unit outputs position information indicating a position of the drive shaft to the servo control simulation unit in the drive shaft simulation step, the servo control simulation unit simulates feedback control of the drive shaft simulation unit using the position information in the servo control simulation step, and the machining condition determining unit evaluates, in the machining result determining step, the machining result obtained when the feedback control of the drive shaft simulation unit is simulated. [12] The machining condition determination method according to claim 11, wherein the servo control simulation unit outputs the position information to the numerical control simulation unit, the numerical control simulation unit simulates feedback control of the servo control simulation unit using the position information, and the machining result evaluation unit evaluates the machining result obtained when the feedback control of the servo control simulation unit and the feedback control of the drive shaft simulation unit are simulated.

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