Method and system for adapting feed speed of feed control on a numerically controlled machine tool

Abstract

A computer-implemented method for providing a setpoint value of a feed speed for adaptive feed control on a numerically controlled machine tool, the method comprising: while machining a workpiece (1) with a tool (2), - (M10) receiving real-time data (101) having a current state of at least one controlled axis (X, Y, Z), - (M20) determining an actual value of at least one cutting force of the tool (2) based on the real-time data, - (M30) receiving lookahead data (102) associated with a predicted state of the at least one controlled axis (X, Y, Z), - (M40) simulating the machining of the workpiece (1) based on the real-time data (101) and based on the lookahead data (102), wherein a simulated value of the at least one cutting force of the tool (2) is generated, - (M50) determining at least one setpoint value (103) of a feed speed of the at least one controlled axis (X, Y, Z) based on the simulated value and the actual value of the at least one cutting force of the tool (2), - (M60) providing the at least one setpoint value (103) of the feed speed of the at least one controlled axis (X, Y, Z).

Description

Technical Field

[0001] The subject matter disclosed in this invention relates to methods and systems for adapting feed rates to feed control.

[0002] Furthermore, the subject matter disclosed in this invention relates to machine-executable components including instructions for performing the method, to machine-readable media including machine-executable components, to computer-readable data carriers having machine-executable components stored thereon, and to data carrier signals carrying machine-executable components.

[0003] The subject matter disclosed in this invention also relates to machine tools including such a system.

[0004] The subject matter disclosed in this invention solves the problem of finding better feed rates. High feed rates can lead to tool breakage (stationary, damaged) or excessive tool wear (high tool cost). Low feed rates result in longer manufacturing times and also increase costs. Background Technology

[0005] One well-known method is to simulate the material removal process and the resulting cutting forces offline to determine the optimal feed rate (see U.S. Patent 4,833,617). The method disclosed in U.S. Patent 4,833,617 does not provide look-ahead data. Furthermore, if there are online modifications, such as a restart of a partially completed run, this can be handled by the online simulation, whereas the previously run offline simulation will only be based on the nominal sequence, leading to incorrect results.

[0006] DE10257229A1 discloses a collision avoidance method that uses stored NC program commands to provide look-ahead simulation to avoid collisions.

[0007] WO2012 / 153157A2 discloses the calculation and prediction of cutting forces. The calculation of cutting forces is also known from US2017 / 227945A1.

[0008] The well-known product implementation method is CGTech's VERICUT.

[0009] Some existing methods have the advantage of being forward-looking in terms of path, but they cannot take into account actual material and tool parameters. The precise values ​​depend on the material batch and the wear of the cutting tool.

[0010] Therefore, there is a need for a system and method that allows for improved feed rate adaptation and optimized machine tool operation during machining. Summary of the Invention

[0011] To achieve this objective, the present invention provides a computer-implemented method for providing setpoint values ​​for the feed rate of adaptive feed control on a CNC machine tool, for example, for milling, turning, grinding, and drilling. The steps of the method are performed while machining a workpiece with a machine tool. The method includes, for example, receiving real-time data associated with the current state of at least one controlled axis using a first interface.

[0012] Real-time data reception can be performed continuously or periodically.

[0013] The method also includes the step of determining the actual value of at least one cutting force of the tool based on real-time data.

[0014] In addition, the method includes the step of receiving (continuously or periodically) look-ahead data associated with the predicted state of at least one controlled axis, for example, using a second interface.

[0015] It can perform the reception of forward-looking data continuously or periodically.

[0016] The method also includes steps of simulating the machining of the workpiece based on real-time and prospective data, such as using a computing unit such as an edge device or a CNC, wherein a simulated value of at least one cutting force of the tool is generated, the simulated value including the value of at least one cutting force of the tool predicted in time increments sufficient to adjust the feed rate before the force peak occurs.

[0017] The simulation of workpiece machining can be performed continuously or periodically.

[0018] Simulations based on actual measurements and forward-looking data allow for the avoidance of instantaneous force peaks that could damage workpieces, tools, components, or machines (especially bearings on spindles).

[0019] In addition, the method includes the following steps: determining at least one setpoint value of the feed rate of at least one controlled axis based on the actual value and simulated value of at least one cutting force of the tool, and providing at least one setpoint value of the feed rate of at least one controlled axis, for example, through a third interface.

[0020] Running the method (and the simulations included in the method) during the manufacturing process allows the benefits of using simulation for forward-looking purposes to be combined with the use of actual values ​​to adapt to reality.

[0021] In other words, it allows the use of systems that implement this method to enhance machine tools to respond to changes in material properties or tool wear and to change the feed rate before actual values ​​show dynamic changes.

[0022] In an embodiment, the real-time data includes data associated with measurements of at least one cutting force of the tool and / or the torque of the spindle and / or the speed and / or position of the tool (e.g., as a 6D tuple of the tool's position and orientation).

[0023] In one embodiment, the actual value of at least one cutting force of the tool is determined by the torque of the spindle. This is advantageous because no additional force sensor is required in this case.

[0024] The force / torque of the feed axis drive can also be used to obtain further information about the cutting force. Furthermore, the position measurement system (encoder) in the machine tool can provide an indication of the cutting force.

[0025] In an embodiment, the prospective data includes data associated with predicted values ​​of the tool’s velocity and / or position (e.g., 6D, position, and orientation).

[0026] In one embodiment, look-ahead data is generated within a predetermined time interval, wherein the predetermined time interval is shorter than the braking time of at least one controlled axis.

[0027] In the embodiments, the length of the predetermined time interval (look-ahead time interval) is from about 10 ms to about 1000 ms, especially 100 ms.

[0028] In the embodiments, the machining of the simulated workpiece includes, in particular, the following:

[0029] - Simulate material removal,

[0030] - (for example, subsequently) calculate at least one cutting force.

[0031] If the workpiece geometry and tool path remain unchanged during execution / machining (i.e., not interrupted by the user, not restarted after partial completion, etc.), material removal calculations can be performed offline. However, the method is still advantageous if cutting force calculations are performed online, as material and tool parameters can be adapted to the actual situation.

[0032] In this embodiment, simulating at least one cutting force involves utilizing at least one of geometric tolerances, material parameters, and tool parameters. These parameters have nominal values ​​and some variations (due to the original workpiece, material batch, tool wear, etc.).

[0033] In an embodiment, determining at least one setpoint value for the feed rate based on at least one simulated cutting force includes:

[0034] - Compare a simulated value of at least one cutting force with an actual value of at least one cutting force, e.g., a sequential comparison.

[0035] - Select at least one setpoint value for the feed rate so that the actual value matches the simulated value.

[0036] In the embodiments, the acquisition / measurement is performed periodically, particularly with a period of about 125 μs to about 5 ms, and more particularly with a period of 2 ms.

[0037] The simulated value of at least one cutting force of the tool includes, or serves as, a predicted (future) value of at least one cutting force of the tool. In other words, a simulation is performed prior to real-time operation.

[0038] The value of at least one cutting force of the tool is predicted in time increments, which are sufficient to adjust the feed rate before the force peak occurs, especially shorter than the braking time of at least one controlled axis, and even more especially about 10 times shorter than the aforementioned look-ahead time interval.

[0039] Adjusting the feed rate before the force peak occurs allows the simulation to use parameters adjusted based on the most recent (e.g., shorter than the measurement cycle mentioned above) measurements characterizing the current material and tooling conditions.

[0040] To achieve the above objectives, the present invention also provides a method for adaptive feed control on a CNC machine tool, wherein the steps of the method are performed when machining a workpiece using a machine tool according to the instructions of the part program.

[0041] The method includes the step of acquiring real-time data associated with the current state of at least one controlled axis.

[0042] The method also includes the step of generating (e.g., calculating) look-ahead data associated with the predicted state of at least one controlled axis, based on the description of the part program, for example using a CNC component.

[0043] In addition, the method includes the step of providing at least one setpoint value of the feed rate of at least one controlled axis according to the above method.

[0044] The method further includes the step of controlling the feed rate of at least one controlled axis using at least one setpoint value of the feed rate, for example using a CNC component.

[0045] To achieve the above objectives, the present invention also provides a machine-executable component including instructions that, when executed by a computing system, cause the computing system to perform the method described above for providing a setpoint value for the feed rate.

[0046] To achieve the above objectives, the present invention also provides a system that can be integrated, for example, into an edge device or a CNC, the system comprising: a memory storing machine-executable components; and a processor operatively coupled to the memory and configured to execute the machine-executable components, wherein the machine-executable components include the aforementioned machine-executable components.

[0047] In an embodiment, the system further includes a numerical control component configured to control at least one axis of a machine tool, the machine tool including a tool, and during the machining of a workpiece with the tool according to the instructions of a part program, acquiring real-time data associated with the current state of at least one controlled axis, generating (e.g., calculating) look-ahead data associated with a predicted state of at least one controlled axis based on the instructions of the part program, transmitting the real-time data and look-ahead data to a machine-executable component, receiving at least one setpoint value of feed rate from the machine-executable component, and using the at least one setpoint value of feed rate to control the feed rate of at least one controlled axis.

[0048] In one embodiment, the numerical control component can be configured to acquire real-time data from a sensor device that measures real-time data.

[0049] Within the scope of this disclosure, the term "component" can refer to one or more software components, one or more hardware components, or a combination of one or more hardware and software components. Attached Figure Description

[0050] The above and other objects and advantages of the present invention will become apparent upon consideration of the following detailed description of certain aspects, which only indicate a few possible modes of practice. The description is taken in conjunction with the accompanying drawings, wherein like reference numerals always denote like parts, and wherein:

[0051] Figure 1 The cross-section of a CNC machine tool is shown schematically.

[0052] Figure 2 The diagram schematically illustrates an adaptive feed control system for a machine tool.

[0053] Figure 3 A flowchart is shown of a computer-implemented method for providing setpoint values ​​for feed rate in adaptive feed control.

[0054] Figure 4 A flowchart of a method for adaptive feed control on a CNC machine tool is shown. Detailed Implementation

[0055] Figure 1A portion of a CNC machine tool is schematically shown. Workpiece 1 is secured to worktable 4. Workpiece 1 is machined by tool 2 (here, a cutting tool), which is fixed to and rotated by spindle 3.

[0056] Tool 2 can move relative to workpiece 1 in three directions: X, Y, and Z. Other machine tools may allow additional movements between tool 2 and workpiece 1 or movements in other directions, for example, via additional pivots.

[0057] The machining process is controlled by a numerical control (NC) system 5 associated with the machine tool. The NC system 5 controls the X, Y, and Z axes of the machine tool. It sends control signals to the machine tool and receives feedback data from the machine tool. Figure 1 (The arrows in the diagram point in two directions). NC System 5 can be designed as a CNC unit.

[0058] Figure 1 A sensor device 6 associated with the machine tool is shown. Sensor device 6 may include multiple different sensors to observe / monitor the machining process and acquire (e.g., by measurement) different measurement data that can be used to estimate the state of tool 2 and / or workpiece 1. The measurement data may include acoustic and / or visual measurements and may be correlated with vibrations of tool 2, motion of tool 2 and / or workpiece 1, etc. Therefore, the sensors may be acoustic, vibration, visual sensors, etc. The visual sensor may be a camera, such as a 3D camera, or based on laser technology. Sensor device 6 transmits the acquired data to NC system 5.

[0059] The NC system 5 includes a part program or NC program 50 and a numerical control (NC) component 51. The basic function of the NC component 51 is to read the part program and drive the X, Y, Z axes and the spindle 3 in the drive controller (not shown) according to the instructions of the part program 50.

[0060] NC component 51 interprets the part program and generates look-ahead data associated with one or more predicted states of one or more controlled axes X, Y, Z. The look-ahead data may, for example, include the velocity distribution for the rotational spindle 3. This allows for smooth and precise motion within the constraints of the driven / controlled axes X, Y, Z.

[0061] In other words, during machining, the movement of tool 2 is limited according to the instructions of part program 50.

[0062] NC part 51 can be designed as a software component.

[0063] It should be understood that part program 50 can be part of NC part 51.

[0064] also, Figure 1An edge device 7 associated with the NC system 5 is shown. The edge device 7 is configured to exchange data with the NC system 5, and in particular with the NC component 51.

[0065] Figure 2 It shows a machine tool (e.g.) Figure 1 The adaptive feed control system 100 for machine tools. In other words, Figure 2 More details are shown about Figure 1 The control aspects of machine tools.

[0066] System 100 includes an NC system 50 comprising one or more drive axes X, Y, Z and / or spindles 3. Furthermore, system 100 includes an edge device 7. The edge device 7 may be designed as an industrial computing device and typically includes a memory device and a processor device, wherein the memory device stores machine-executable components, and the processor device is operatively coupled to the memory device and configured to execute the machine-executable components.

[0067] The edge device 7 includes a machine-executable situation-aware module 70 for providing a setpoint value for the feed rate of adaptive feed control on the machine tool.

[0068] In an embodiment, the situation awareness module 70 may be part of or integrated into the NC system 5.

[0069] During the machining of workpiece 1 using tool 2, situation sensing module 70 receives, for example, information via first interface 71 (see example). Figure 3 Real-time data 101 associated with the current state of the controlled axes X, Y, Z (or step M10 in step 4).

[0070] Real-time data 101 is acquired. For example, by measurement performed by the CNC component 51 via the sensor device 6 (see example). Figure 4 (Step S10 in the process). The NC component 51 then sends the real-time data 101 to the situation awareness module 70.

[0071] Real-time data 101 can be received continuously or periodically by the situation awareness module 70.

[0072] Real-time data 101 can be continuously or periodically acquired or measured by sensor device 6.

[0073] In the embodiments, the acquisition or measurement is performed periodically, particularly with a period of about 125 μs to about 5 ms, and more particularly with a period of 2 ms.

[0074] Real-time data 101 may include data associated with measurements of the cutting force of tool 2 and / or the torque of spindle 3 and / or the speed of tool 2 and / or the position of tool 2. The position of the tool may be a six-dimensional vector containing information about the position and orientation of tool 2.

[0075] Based on real-time data, the situation awareness module 70 determines (see example) Figure 3 The actual value of the cutting force of tool 2 in step M20 of step 4.

[0076] Those skilled in the art will understand that the calculation of the actual value of the cutting force can be performed, for example, by the NC component 51 or by the situation-aware module 70, such that if the cutting force is calculated before reaching the situation-aware module 70, then "determining the actual value of the cutting force of tool 2" can mean reading out. The actual value of the cutting force can be calculated, for example, by the NC component 51 based on the torque of the spindle.

[0077] In addition, the situation awareness module 70 receives, for example, look-ahead data 102 associated with the predicted state of the controlled axes X, Y, Z via the first interface 71.

[0078] It should be understood that the situation awareness module 70 may include different interfaces for receiving real-time data 101 and look-ahead data 102.

[0079] Situation awareness module 70 receives continuously or periodically (see example) Figure 3 Or step M30 in 4) prospective data 102.

[0080] Forward data 102 is generated (determined or calculated) by NC part 51 based on the description of part program 50 (see example). Figure 4 Step S20 in the process.

[0081] Forward data 102 can be generated for a predefined time interval, wherein, in particular, the predefined time interval is shorter than the braking time of the controlled axes X, Y, Z.

[0082] The length of the predetermined time interval (look-ahead time interval) can vary from approximately 10 ms to approximately 1000 ms. In this embodiment, the look-ahead interval is approximately 100 ms.

[0083] Based on real-time data 101 and prospective data 102, the situation awareness module 70 simulates (see example...) Figure 3 Alternatively, in step M40 of step 4, the workpiece 1 is machined, and a simulated value of the cutting force of tool 2 is generated.

[0084] The machining of the simulated workpiece 1 may include, for example, simulating material removal, followed by calculating the cutting force.

[0085] If the workpiece geometry and tool 2 path are not modified during execution (i.e., not interrupted by the user, not restarted after partial completion, etc.), the material removal calculation steps can be performed offline. However, it is still beneficial if the cutting force simulation is performed entirely online, as the material and tool parameters can be adapted to reality.

[0086] Furthermore, the simulation of cutting forces can utilize geometric tolerances, material parameters, tool parameters, or combinations thereof. Each of these has a nominal value and some variation (original workpiece, material batch, tool wear, etc.).

[0087] The simulated value of the cutting force of tool 2 can include or can be the predicted value of the cutting force of tool 2. The simulation can be performed in advance (look-ahead simulation of the cutting force).

[0088] In this embodiment, the cutting force of tool 2 is predicted using a time increment sufficient to adjust the feed rate before the force peak occurs. In particular, the time increment can be shorter than the braking time of the controlled axes X, Y, Z, and more particularly, about 10 times shorter than the aforementioned look-ahead time interval.

[0089] The situation-aware module 70 can run simulations continuously or periodically.

[0090] Based on the simulated and actual values ​​of the cutting force of tool 2, the situation-aware module 70 determines (calculates) the setpoint values ​​of the feed rates of the controlled axes X, Y, and Z (see example...). Figure 3 Or step M50 in 4).

[0091] Determining the setpoint value of the feed rate based on at least one simulated cutting force may include comparisons, such as continuously comparing the simulated value of the cutting force with the actual value of the cutting force, and selecting a setpoint value of the feed rate such that the actual value matches the simulated value.

[0092] Then, the situation awareness module 70 provides a setpoint value (see, for example...) Figure 3 Or step M60 in 4). Figure 2 An embodiment is shown that provides setpoint values ​​to NC component 51 using the second interface 72 (see, for example...). Figure 4 Step S30 in the process.

[0093] The action of providing the above setpoint value is performed during the machining process (i.e., online).

[0094] Subsequently, NC component 51 utilizes (for example, see...) Figure 4 The feed rate setpoint value provided in step S40) is used to control the feed rate of the controlled axes X, Y, and Z.

[0095] In the same manner, the situation-aware module 70 can (additionally) provide setpoint values ​​for the speeds of the controlled axes X, Y, and Z, so that the NC component 51 can adjust the speed accordingly.

[0096] Figure 3 A flowchart is shown of a computer-implemented method M1 for providing setpoint values ​​for feed rate used in adaptive feed control on a CNC machine tool. Method M1 can be implemented in... Figure 2 The method is implemented on system 100. It is performed during the machining of workpiece 1 using tool 2 and includes the following steps:

[0097] M10 receives real-time data 101 associated with the current state of at least one controlled axis X, Y, Z.

[0098] M20 determines the actual value of at least one cutting force of tool 2 based on real-time data.

[0099] M30 receives look-ahead data 102 associated with the predicted state of at least one controlled axis X, Y, Z.

[0100] M40 simulates the machining of workpiece 1 based on real-time data 101 and look-ahead data 102, wherein at least one simulated value of the cutting force of tool 2 is generated.

[0101] Based on the simulated and actual values ​​of at least one cutting force of tool 2, M50 determines at least one setpoint value 103 for the feed rate of at least one controlled axis X, Y, Z, and...

[0102] M60 provides at least one setpoint value 103 for the feed rate of at least one controlled axis X, Y, Z.

[0103] Figure 4 A flowchart of a computer-implemented method S1 for adaptive feed control on a CNC machine tool is shown. Method S1 can be implemented in... Figure 1 In the scenario shown Figure 2 The method is implemented on system 100. It is performed during the machining of workpiece 1 using tool 2 according to the instructions of part program 50, and includes the following steps:

[0104] S10 acquires real-time data 101 associated with the current state of at least one controlled axis X, Y, Z.

[0105] Based on the description of part program 50, S20 generates look-ahead data 102 associated with the predicted state of at least one controlled axis X, Y, Z.

[0106] S30 is based on a method for providing a setpoint value for the feed rate of adaptive feed control on a CNC machine tool, for example, according to... Figure 3Method M1 provides at least one setpoint value 103 for the feed rate of at least one controlled axis X, Y, Z.

[0107] S40 uses at least one setpoint value 103 of the feed rate to control the feed rate of at least one controlled axis X, Y, Z.

[0108] It should be understood that step 30 includes at least the following: Figure 3 The steps of method M1 may include corresponding method steps according to one or more embodiments of the system described herein.

[0109] In summary, compared with offline simulation, adapting the simulation parameters of the material removal and cutting force models can produce higher prediction accuracy, enabling higher feed rates (lower production time) without the risk of overload.

[0110] The embodiments of the invention described above are presented for illustrative purposes and not for limitation. In particular, the embodiments described with respect to the accompanying drawings are merely a few examples of the embodiments described in the introductory section. The technical features described with respect to the system can be applied to enhance the methods disclosed herein and vice versa.

Claims

1. A computer-implemented method for providing a setpoint value for the feed rate of adaptive feed control on a CNC machine tool, the method comprising: When machining workpiece (1) with tool (2), - Step M10, receive real-time data (101) associated with the current state of at least one controlled axis (X, Y, Z). - Step M20, based on the real-time data, determine the actual value of at least one cutting force of the tool (2), - Step M30, receive look-ahead data (102) associated with the predicted state of the at least one controlled axis (X, Y, Z). - Step M40, simulating the machining of the workpiece (1) based on the real-time data (101) and the prospective data (102), wherein a simulated value of at least one cutting force of the tool (2) is generated, the simulated value including the value of the at least one cutting force of the tool (2) predicted in time increments sufficient to adjust the feed rate before the force peak occurs. - Step M50, based on the simulated value and the actual value of the at least one cutting force of the tool (2), determine at least one setpoint value (103) of the feed rate of the at least one controlled axis (X, Y, Z). - Step M60, providing at least one setpoint value (103) for the feed rate of the at least one controlled axis (X, Y, Z). The feed rate of the at least one controlled axis is controlled using the at least one setpoint value of the feed rate.

2. The method according to claim 1, wherein, The real-time data (101) includes data associated with measurements of at least one cutting force of the tool (2) and / or the torque of the spindle (3) and / or the speed of the tool (2) and / or the position of the tool (2).

3. The method according to claim 1 or 2, wherein, The forward-looking data (102) includes data associated with predicted values ​​of the speed and / or position of the tool (2).

4. The method according to any one of claims 1 to 2, wherein, The look-ahead data (102) is generated for a predetermined time interval, wherein the predetermined time interval is shorter than the braking time of the at least one controlled axis (X, Y, Z).

5. The method according to claim 4, wherein, The predetermined time interval is used as a look-ahead time interval, and the length of the predetermined time interval is from 10 ms to 1000 ms.

6. The method according to claim 5, wherein, The predetermined time interval is 100 ms in length.

7. The method according to any one of claims 1 to 2, wherein, The machining of the workpiece (1) in step M40 includes the following: - Simulate material removal, - Calculate the at least one cutting force.

8. The method according to claim 7, wherein, The machining of the workpiece (1) is simulated by the following: simulating material removal and calculating the at least one cutting force.

9. The method according to any one of claims 1 to 2, wherein, The simulation of the at least one cutting force in step M40 includes: - Utilize at least one of geometric tolerances, material parameters, or tooling parameters.

10. The method according to any one of claims 1 to 2, wherein, Determining the at least one setpoint value (103) of the feed rate based on at least one simulated cutting force in step M50 includes: - Compare the simulated value of the at least one cutting force with the actual value of the at least one cutting force. - Select at least one setpoint value for the feed rate such that the actual value matches the simulated value.

11. The method according to any one of claims 1 to 2, wherein, The time increment is shorter than the braking time of the at least one controlled axis (X, Y, Z).

12. The method according to any one of claims 1 to 2, wherein, The actual value of the at least one cutting force of the tool is determined from the torque of the spindle.

13. The method according to any one of claims 1 to 2, wherein, The forward-looking data includes data associated with predicted values ​​of the tool's speed and / or location.

14. A method for adaptive feed control on a CNC machine tool, the method comprising: When machining workpiece (1) with tool (2) according to the part program instructions, - Step S10: Obtain real-time data (101) associated with the current state of at least one controlled axis (X, Y, Z). - Step S20, based on the description of the part program, generate prospective data (102) associated with the predicted state of the at least one controlled axis (X, Y, Z). - Step S30, according to any one of claims 1 to 13, providing at least one setpoint value (103) of the feed rate of the at least one controlled axis (X, Y, Z). - Step S40, using the at least one setpoint value (103) of the feed rate to control the feed rate of the at least one controlled axis (X, Y, Z).

15. The method according to claim 14, wherein, The acquisition is performed periodically.

16. The method according to claim 15, wherein, The acquisition is performed in cycles ranging from 125 μs to 5 ms.

17. The method according to claim 15, wherein, The acquisition is performed in 2 ms cycles.

18. A machine-executable component comprising instructions which, when executed by a computing system, cause the computing system to perform the method according to any one of claims 1 to 13.

19. A system comprising a memory and a processor, wherein, The memory stores machine executable components, wherein the processor is operatively coupled to the memory and configured to execute the machine executable components, wherein the machine executable components include the machine executable component (70) according to claim 18.

20. The system of claim 19, further comprising: A numerical control unit (51) is configured to control at least one axis (X, Y, Z) of a machine tool, the machine tool including a tool (2) and during the machining of a workpiece (1) with said tool (2) according to the instructions of the part program, - Acquire real-time data (101) associated with the current state of the at least one controlled axis (X, Y, Z). - Based on the description of the part program, generate look-ahead data (102) associated with the predicted state of the at least one controlled axis (X, Y, Z). - The real-time data (101) and the prospective data (102) are transmitted to the machine-executable component (70). - Receive at least one setpoint value (103) of the feed rate from the machine-executable component (70), and - The feed rate of the at least one controlled axis (X, Y, Z) is controlled by using the at least one setpoint value (103) of the feed rate.

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