Method of operating a machine tool

Abstract

The invention relates to a computer-supported method for operating a machine tool (1), wherein the machine tool (1) comprises at least two moving axes (X1, Y1, Z1, X2, Z2), wherein, in a predetermined time period, first and second data is recorded, wherein * the first data represents axial movements of the individual axes (X1, Y1, Z1, X2, Z2) and is based on measurements within the machine tool (1), and * the second data comprises control commands for the individual axes (X1, Y1, Z1, X2, Z2), the first and the second data is evaluated in order to assign the control commands to the axial movements for each axis (X1, Y1, Z1, X2, Z2), one or more types of axial movement are determined for each axis (X1, Y1, Z1, X2, Z2), one or more signals are generated in order to visualise the one or more types of axial movement, determined for each axis (X1, Y1, Z1, X2, Z2), in the form of an aggregated view (PA), based on the aggregated view (PA), it is reported which type of axial movement during operation of the machine tool lasts the longest in the predetermined time period.

Description

[0001] Description

[0002] Method for operating a machine tool

[0003] Regardless of the gender of the animate nouns used in this revelation, they include any gender identity and any ethical sex.

[0004] The present disclosure relates to a computer-aided method for operating a machine tool, wherein the machine tool comprises at least two movable axes.

[0005] In addition, a computing unit is disclosed which is set up for data transmission with a machine tool and is configured to interact with the machine tool in such a way that the aforementioned method is carried out.

[0006] In addition, a computer program is disclosed which comprises computer program code which enables the aforementioned computing device to carry out the aforementioned method - in the context of interaction with the machine tool.

[0007] Finally, a computer-readable medium on which such a computer program is stored is disclosed.

[0008] In the field of machine tools, increasing productivity, for example, reducing workpiece processing time, is a very important issue alongside workpiece quality. However, it is often not always clear where there is potential in the overall machining process to accelerate machining.

[0009] To date, process optimizations aimed at reducing processing times have typically been achieved by separately examining individual processes, identifying where there is potential for time savings within them. This is complex, and often significant process accelerations within a single process step result in little savings in terms of overall processing time because other processes dominate.

[0010] Computer-aided operating methods are known from the prior art in which the speed of movement of machine parts can be adjusted. For example, a patent application with the publication number WO 9709547 A1 shows an operating method in which a computer-aided design program can be configured to model a kinematic speed profile of a point on the machine to be controlled. A graphical user interface on the computer enables an operator to select desired speed points for a motor drive that controls the movement of the point on the machine. A curve fit is applied to the speed points in order to realize a desired speed profile for the motor drive and the point on the machine.The desired velocity profile is then integrated and scaled to obtain a scaled velocity profile that realizes an actual or desired displacement of the point according to the operation of the machine. By controlling the operation of elements of a machine with velocity profiles, the coordination of related elements and points on the machine can be visualized by an operator selecting the velocity points for each drive of the machine. A method for implementing the same is also disclosed.

[0011] It is therefore desirable to provide means to better reduce the duration of processes carried out by machine tools, preferably manufacturing processes, for example workpiece machining processes or additive manufacturing processes.

[0012] The above-mentioned object can be achieved with a method of the aforementioned type, wherein first and second data are acquired within a predetermined time interval. The first data are representative of axis movements of the individual axes. Preferably, the first data are acquired for all axes of the machine tool. Furthermore, the first data are based on measurements taken with sensors arranged in the machine tool.

[0013] The process preferably runs in real time, i.e. while the machine tool is running, so that appropriate corrections and changes can be made while the machine is running.

[0014] The second data includes control commands for the individual axes. These can be, for example, program commands (e.g., G-code) and / or PLC signals. PLC stands for Programmable Logic Controller.

[0015] The first and second data are evaluated to assign the control commands to the axis movements for each axis, preferably immediately or directly. In particular, this creates a cross-relationship between the first and second data, which, for example, makes it possible to reference axis movements to corresponding control commands, preferably to corresponding parts program sections.

[0016] In addition, one or more types of axis movements are determined for each axis, for example based on the assignment carried out. It is also conceivable that the types of axis movements are determined or ascertained directly from the first data. The types of axis movements can be different. This means that in the predetermined time period, each axis can carry out one or more types of axis movements, e.g. stand still, move at a constant speed, accelerate or brake. This makes it possible, for example, to determine whether and when the respective axis is involved in a process carried out during operation of the machine tool, in particular a manufacturing process. In addition, the current line in the part program can be determined at the time of an event and the downtimes can be assigned to the respective subroutines and cycles.

[0017] One or more signals are then generated to visualize the one or more types of axis movement determined for each axis in the form of an aggregated view.

[0018] The signals can, for example, be generated with the aid of the first and / or second data. In this case, it can be expedient to collect data from the first and / or second data based on certain criteria. For example, the data from the first and / or second data that can be assigned to a certain type of axis movement performed by all axes (involved in the machining process) can be aggregated. This means that the aggregated view can show which types of axis movement are performed by all axes and what the relationship (in terms of time) looks like between the individual (movement) types.

[0019] In other words, in the aggregated view, commonalities of the movements of the individual axes (those involved in the machining process), in particular all axes, are summarized and displayed.

[0020] The aggregated view reports which type of axis movement takes the longest during machine tool operation in the predetermined time period.

[0021] The aggregated view, for example, makes it possible to visualize the respective proportions and types of axis movements that are performed by multiple axes simultaneously, and in particular by all axes, during the predetermined time period. This makes it quickly apparent within the overall process which individual processes or individual movements have the greatest potential, for example, to reduce process time. For example, the times when all axes are stationary could be spent performing any communication tasks between the control partner, such as a CNC (a CNC controller) and PLC, and this could represent a potential source of savings.

[0022] The aggregated view is thus generated using the signals that represent the information on the types of axis movements obtained from the initial data, i.e., the measured data. Since, as discussed above, the initial data is associated with the control commands, the aggregated view allows for the identification of the control commands and, in particular, the part program sections corresponding to the respective type of axis movement. Through such referencing, the user can directly find these control commands and edit them to optimize and, in particular, shorten processing time.

[0023] It goes without saying that a machine tool can be a CNC machine or a robot or robot arm, since a robot—from a control engineering perspective—can be considered a machine tool with robot kinematics. Robots primarily have rotary axes.

[0024] The message can be designed in different ways. For example, it is conceivable that the longest-lasting type of axis movement could be indicated on a display using a predefined color. However, the message can also be provided with the aid of a text and / or audio message to improve the message's perceptibility in certain cases or for a specific group of people.

[0025] In one embodiment, it may be provided that one or more measures to reduce the duration are proposed, at least for the determined type of axis movement. This can be any measure from the group comprising: increasing axis dynamics, in particular jerk, acceleration, and speed; increasing process speed; and reducing non-productive times, in particular tool change time.

[0026] In one embodiment, it can be provided that the types of axis movements include dynamic components of the axis movements as well as standstills of the axes - that is, movements of a constant type over a time interval or constant movement in the time interval.

[0027] For example, "standstill" is a movement with a constant speed equal to zero.

[0028] It can be useful if each dynamic component of the axis movements is from the group which includes: axis movements with constant jerk, constant acceleration, constant speed (constant travel).

[0029] If the sections of the process carried out in the predetermined time period are known, it can be determined automatically, for example, when and how the individual axes are involved in the overall process or are at a standstill.

[0030] In one embodiment, it may be provided that the first data is high-frequency data.

[0031] High-frequency data acquisition, e.g. via an edge device, can facilitate the simultaneous recording of the axis movements of all axes (involved in the process).

[0032] The term "high-frequency" in the context of the present disclosure means that the data is collected / acquired at (preferably typical) clock frequencies of the control of the machine tool or the drive of the respective axis. For example, this may be position data of the axes that are acquired in a position control cycle of the control or the drive. In one embodiment, it may be provided that the predetermined time period corresponds to a manufacturing process stage, in particular a machining operation.

[0033] In one embodiment, it may be possible to adjust the depth of data evaluation. For example, it is also possible to evaluate the constant-speed ranges with regard to the speed level in order to show in more detail whether the axes are moving at GO, i.e., rapid traverse, or are limited by process speeds.

[0034] This information can be particularly useful when comparing the machining performance of two or more machine tools. This allows you to determine whether they are running, or have been running, at different process speeds. Furthermore, the process speed of the respective machine tool can be optimized.

[0035] The task can also be solved using the computing device mentioned above.

[0036] In one embodiment, the computing device may comprise one or more interconnected computing units that exchange data. The computing units may be spatially separated from one another.

[0037] It is understood that data transmission (or data transfer; English: data transmission) in information technology is the exchange of digital data between two or more spatially distant senders and receivers via cables or radio links.

[0038] In one embodiment, it can be provided that the computing device and in particular the data acquisition systems contained therein have a memory depth that is sufficient to enable data collection over the entire manufacturing / processing process.

[0039] The invention and further advantageous embodiments of the invention are explained in more detail using exemplary embodiments shown in principle, in which:

[0040] FIG 1 shows a machine tool with a computing device, FIG 2 shows a visualization of the types of axis movement of the individual axes and an aggregated view, and

[0041] FIG 3 a flow chart of a computer-aided process.

[0042] FIG. 1 shows a machine tool 1 with axes XI, Y1, and ZI. The machine tool 1 is communicatively connected to a computing device 2. In particular, the data transmission between the machine tool 1 and the computing device can proceed according to one or more communication protocols.

[0043] The machine tool 2 is designed to machine a workpiece 4 with a tool 3.

[0044] The computing device 2 comprises, for example, an NC controller 20 and a server or a computer 21, which can be connected to the controller 20 via a network 22. The network 22 can be a public network, e.g., the Internet, or a private network.

[0045] Several sensors (not shown here) are mounted on the machine tool 1. Preferably, physical and virtual sensors are present on the machine tool 1. The sensors supply data to the computing device 2 during a machining operation.

[0046] The data includes the first data, which are representative of the axis movements of the individual axes XI, Y1, ZI, and X2, Z2 (not shown here), and are based on measurements taken by the sensors. Furthermore, the computing device 2 has access to second data, which includes control commands for the individual axes.

[0047] The computing device 2, preferably the server 21, is configured to evaluate the first and second data in order to assign the control commands to the axis movements for each axis.

[0048] During the assignment, dynamic components of the axis movements can be assigned to respective sections of the NC program code. The dynamic components can be, for example, constant jerk, constant acceleration, or constant speed.

[0049] The assignment is preferably performed for each axis. This allows the current line in the part program to be determined at the time of an event and the downtimes to be assigned to the respective subroutines and cycles.

[0050] The computing device 2 can also be configured to adjust the depth of the data evaluation or to have it adjusted. For example, it is also possible to evaluate the constant speed ranges with regard to the speed level in order to show in more detail whether the axes are moving at GO, i.e., rapid traverse, or are limited by process speeds.

[0051] The computing device 2 is also configured to generate signals in order to visualize the dynamic components of the axis movement for each axis individually and in particular for all axes involved in the machining process in aggregated form.

[0052] The visualization can be performed on a display device of the NC control 20 and / or the computer 21. Figure 2 illustrates one possible type of visualization. Pie charts or circle diagrams Px are shown. l f Py l fPz2, Px2, Pz2, for each of the five axes XI, Yl, ZI, X2, Z2 of machine tool 1 and a pie chart diagram P A for all axes involved in the machining process in aggregated form - aggregated view. Each diagram Px l f Pyi, Pz l f Px 2 f Pz2, P A It can be seen that the most common types of movement are constant speed and standstill. Based on the aggregated analysis P A It can be seen that constant speed dominates the machining process. This means that in the present example, all axes XI, Yl, ZI, X2, Z2 are moved simultaneously at a constant speed most of the time. The second most common time is when all axes XI, Yl, ZI, X2, Z2 are stationary (dark hatched area). The remaining time of the machining process is spent dynamically moving all axes simultaneously, for example, accelerating or braking.

[0053] Once the dynamic component dominating the machining process has been determined, a message is displayed.

[0054] The message can take different forms. FIG. 2 shows that the part of the pie chart corresponding to the longest dynamic component is highlighted in color and described with text.

[0055] The computing device 2 can be configured to propose one or more measures for reducing the duration of the determined dynamic component of the axis movement.

[0056] For example, the recommendation may be to increase the speed (here constant) to save time. The recommendation may be made on the display of the NC controller 20 or the server 21.

[0057] The visualization of the individual processes of an overall machining process when machining a component shows their contributions and thus enables a simple assessment of the effort and benefit of optimizing these sub-processes with the aim, for example, of reducing the overall machining time.

[0058] FIG 3 shows a flow chart of a computer-aided method for operating a machine tool, for example the machine tool 1 of FIG 1.

[0059] In a step 100, the data—that is, the first and second data—are acquired. The first data is, for example, real-time data based on sensor measurements. The second data includes, for example, the part program code.

[0060] In step 101, the data is evaluated. In particular, parts of the part program code are assigned to specific axis movements.

[0061] In step 102, dynamic components or dynamic components of the axis movements are determined for each individual axis. Their connection to specific parts of the part program code is already known from step 101.

[0062] In a step 103, signals are generated to visualize the dynamic components for the individual axes and for the aggregated view.

[0063] The aggregated view of the dynamic components is visualized in step 104.

[0064] From this, in step 105 the dominant dynamic component during the recorded machining process is determined and reported.

[0065] The purpose of this description is merely to provide illustrative examples and to indicate further advantages and special features of this invention. Thus, it cannot be interpreted as a limitation of the field of application of the invention or of the patent rights claimed in the claims. In particular, the features disclosed in connection with the methods described herein can be usefully used to further develop the devices described herein, and vice versa.

Claims

Patent claims 1. Computer-aided method for operating a machine tool (1), wherein the machine tool (1) comprises at least two movable axes (XI, Yl, ZI, X2, Z2), wherein - first and second data are recorded in a predetermined time period, wherein * the first data are representative of axis movements of the individual axes (XI, Yl, ZI, X2, Z2) and are based on measurements within the machine tool (1), and * the second data includes control commands for the individual axes (XI, Yl, ZI, X2, Z2), - the first and second data are evaluated to assign the control commands to the axis movements for each axis (XI, Yl, ZI, X2, Z2), - one or more types of axis movement are determined from the first data for each axis (XI, Yl, ZI, X2, Z2), - one or more signals are generated to represent the one or more types of axis movement determined for each axis (XI, Yl, ZI, X2, Z2) in the form of an aggregated view (P A ) to visualize, - based on the aggregated view (P A ) which type of axis movement takes the longest during operation of the machine tool in the predetermined time period.

2. Method according to claim 1, wherein one or more measures for reducing the duration are proposed at least for the determined type of axis movement.

3. The method according to claim 2, wherein each measure is from the group comprising: increasing axis dynamics, in particular jerk, acceleration, increasing speed; increasing process speed; reducing non-productive times, in particular tool change time.

4. Method according to one of claims 1 to 3, wherein the Types of axis movements dynamic components of the axis movements as well as standstills of the axes (XI, Yl, ZI, X2, Z2).

5. The method of claim 4, wherein each dynamic portion of the axis movements is from the group comprising: axis movements with constant jerk, constant acceleration, constant velocity.

6. The method according to any one of claims 1 to 5, wherein the first data is high frequency data.

7. Method according to one of claims 1 to 6, wherein the control commands comprise program commands and / or PLC signals.

8. Method according to one of claims 1 to 7, wherein the predetermined time period corresponds to a manufacturing process stage, in particular a machining operation.

9. Computing device (2) which is set up for data transmission with a machine tool (1) and is configured to interact with the machine tool (1) and to carry out a method according to one of claims 1 to 8.

10. A computer program comprising instructions enabling a computing device (2) according to claim 9 to execute a method according to one of claims 1 to 8.

11. A computer-readable medium on which a computer program according to claim 10 is stored.

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