Manufacturing method and machine tool

Abstract

The invention relates to a manufacturing method in which stress parameters are detected in a multidimensional raster and are divided into size classes. In the process, the frequency of events is ascertained. In other words, how often the stress parameters have a value within the different size classes is counted. The counting process can run over the entire usage duration of the machine tool or individual processing steps or sub-processing steps. The stress parameters can describe load, wear, and / or usage variables, and the stress parameters can be directly measured or can be derived from measured operating parameters. By analyzing the ascertained numbers in the size classes, maintenance measures and / or other processing steps can be controlled. In particular, the maintenance measures and / or the other processing steps are carried out on the basis of the ascertained numbers. In particular, the manufacturing method according to the invention allows a contextual recording and analysis of the processing steps which have been carried out while requiring a small amount of storage without allowing the processing steps which are actually carried out to be reconstructed from the stored numbers.

Description

[0001] Manufacturing processes and machine tools

[0002] Background of the invention

[0003] The invention relates to a manufacturing method in which a workpiece is machined with a machine tool, wherein at least one operating parameter of the machine tool is measured during the machining process. The invention further relates to a machine tool with a tool for machining a workpiece and with a sensor device for detecting at least one operating parameter during machining of the workpiece with the tool.

[0004] Such a manufacturing process and such a machine tool are known, for example, from DE 20 2016 001 105 Ul.

[0005] During the lifetime of a machine tool, a wide variety of loads and consumptions arise due to its use. Operating parameters related to these loads and consumptions can generally be measured and recorded using sensors. However, over long periods of use, this requires considerable storage space, especially if the relevant operating parameters change rapidly. Furthermore, the immediate storage of operating parameters can enable reconstruction of completed machining operations. Therefore, machine tool users will generally not want to make this raw data available to a maintenance service provider or machine manufacturer.

[0006] In principle, it is conceivable to calculate loads and consumption using models based on the machining operations performed and the operating parameters measured during the process. However, the subsequent generation of theoretical load and consumption curves often only partially reflects reality, as the actual curves can be influenced by random variables, particularly wear and tear on the machine tool.

[0007] DE 10 2018 007 905 A1 describes a method for recording and monitoring the history of a work spindle. The following data is recorded in a non-volatile manner: the identification data of the work spindle, the software and hardware revision levels, the parameter data of the installed sensors, the pure process data and / or the filtered maximum and minimum values, and the diagnostic data of all sensors. The process data describes the temporal progression of the sensor parameters.

[0008] From the aforementioned DE 20 2016 001 105 U1, a welding or cutting system with a torch is known. Communication takes place between the torch and a power supply or a control system. The control system monitors and tracks the use of the torch and its respective components. The control system then uses this information to inform a user about the remaining service life or an imminent failure of a torch component. A monitoring device can include at least one accumulator for totaling a first torch utilization factor based on a selected welding parameter or a selected combination of parameters. The accumulator has an output signal representing the sum of the main parameters. When a monitored torch utilization factor reaches a certain value, an action signal is generated.

[0009] Object of the invention

[0010] It is an object of the invention to enable an efficient evaluation of the stress on a machine tool.

[0011] Description of the invention

[0012] This object is achieved according to the invention by a manufacturing method according to claim 1 and a machine tool having the features recited in claim 16. The subclaims and the description specify advantageous embodiments.

[0013] According to the invention, a manufacturing method is provided in which a workpiece is machined using a machine tool. The machine tool can be used for sheet metal processing; in other words, it can be a sheet metal processing method. During processing, the workpiece can be cut out of a blank, for example, a sheet metal panel. The machine tool can, in particular, be a laser processing machine, for example, a laser cutting machine or a laser welding machine. During processing, a laser cutting process or a laser welding process can be carried out. Alternatively, the machine tool can be, for example, a punching machine. The manufacturing method according to the invention is preferably carried out using a machine tool according to the invention, as described below.

[0014] During machining, at least one operating parameter of the machine tool is measured in step A). ​​Preferably, at least two, particularly preferably at least three, operating parameters are measured. The machine tool can have a sensor device for this purpose. The at least one operating parameter can, in particular, describe a current state during the ongoing machining process.

[0015] The at least one operating parameter can be selected, for example, from

[0016] - Position, in particular of a tool of the machine tool, in particular along a machine axis of the machine tool,

[0017] - Acceleration, especially of the tool, especially along the machine axis,

[0018] - Current consumption, power and / or torque of a drive, especially the machine axis,

[0019] - Machining force of the tool of the machine tool,

[0020] - Power output of the machine tool, in particular laser power of a laser processing head,

[0021] - pressure and / or volume flow of a process gas,

[0022] - Time increment over which another operating parameter assumes a certain value,

[0023] - temperature, in particular of a tool of the machine tool, and / or

[0024] - Scattered light, in particular the intensity of the scattered light reflected from the workpiece.

[0025] According to the invention, several size classes are predefined for at least one stress parameter of the machine tool. The size classes enable a classification and simple recording of the processes relevant to the stress on the machine tool. During machining of the workpiece, in a step B), the at least one stress parameter is calculated from the at least one measured operating parameter. In the simplest case, the stress parameter can correspond to the operating parameter. The stress parameter can be calculated by weighting the values ​​of the operating parameter.

[0026] Furthermore, during the machining of the workpiece, in a step C), a count is stored of how often the at least one stress parameter lies within each of the size classes. In other words, the number of times the stress parameter assumes a value that falls within the predefined size classes is counted. The memory requirement is therefore determined by the number of stress parameters and the number of size classes. In particular, the memory requirement does not increase (or at most only insignificantly) with increasing machining time, since only the numbers (numerical values) stored for the different size classes change, but generally no new values ​​are added.

[0027] The stored number of stress events falling into a size class allows for analysis and evaluation of the stress on the machine tool. This creates a history of the machine tool's life cycle that can be used for other applications. The stored information can be used, for example, for diagnostic purposes, particularly for identifying components at risk of wear, for controlling maintenance measures, and for controlling other machining processes. The aggregated storage of stress events differentiated by size class simplifies both the storage itself and the evaluation. Furthermore, it prevents the stored data from being used to draw conclusions about the specific machining processes performed.

[0028] Preferably, the at least one stress parameter is calculated from at least two operating parameters, in particular by multiplication or division. This allows for a more in-depth assessment of the stresses on the machine.

[0029] Particularly preferably, the at least one stress parameter is calculated using the time period over which a respective operating parameter was measured. In particular, the at least one operating parameter can be multiplied by a corresponding time increment over which it assumed a specific value, or divided by the time increment. The former allows, in particular, the determination of consumption data in the sense of integration over time. For example, an energy input can be determined from a laser power, which can represent a load on a tool support, such as a support web. The latter allows, in particular, the determination of performance data that can be used for wear analysis.

[0030] Preferably, at least two, particularly preferably at least three, stress parameters are calculated. This allows the stress analysis to be further refined.

[0031] Particularly preferably, the at least two stress parameters are calculated for the same time points and assigned to a magnitude class for the multiple stress parameters. The recording and analysis of the treatment thus takes place in a multidimensional grid, with each magnitude class being defined by two parameter values ​​for each of the stress parameters under consideration. In this way, the occurring loads, for example, mechanical loads and / or consumption, can be recorded and analyzed in their respective physical context. In particular, interdependencies between multiple operating parameters or multiple stress parameters can be considered or recognized.

[0032] Steps B) and C), and preferably also A), can be performed at a fixed frequency. The frequency is preferably at least 10 Hz, more preferably at least 100 Hz, and most preferably at least 500 Hz. In this way, even rapidly changing processes, which can occur in fractions of a second during laser processing, for example, can be precisely recorded and efficiently processed further through classification and aggregation.

[0033] The size classes for the at least one or more of the stress parameters can each encompass the same range of values. In other words, the size classes can be evenly distributed. This is useful if the stress parameter or underlying operating parameter is not directly related to the mechanical structures of the machine tool.

[0034] Alternatively or additionally, the size classes for the at least one or more of the stress parameters can encompass different value ranges. The classification of the determined values ​​of the stress parameter can thus be adapted, for example, to the mechanical structures of the machine tool. In particular, size classes with larger and smaller value ranges can alternate. In this way, for example, the sequence of support webs of a workpiece support and the gaps between them can be traced in order to record the stress on the support webs, for example, due to the introduction of laser radiation.

[0035] Step C) can be performed over the entire operating life of the machine tool. In other words, the stress events within the respective size classes are counted over the entire operating life of the machine tool. This allows the stress on the machine tool to be evaluated over its entire service life. This variant is particularly suitable for diagnosing machine wear and for planning maintenance and repair measures.

[0036] Alternatively or additionally, step C) can be repeated for each additional blank, workpiece, or contour being machined. In other words, the stress events within the respective size classes are counted for the machining of the respective blank, workpiece, or contour. In this way, loads and / or consumption can be recorded and evaluated on a machining-related basis. This makes it possible to allocate wear-related and / or consumption-dependent machining costs to the respective blank, workpiece, or contour.

[0037] It may be provided that maintenance, repair, and / or replacement of at least one component of the machine tool is carried out if the quantities determined in step C) meet a predefined criterion. The aforementioned measures can thus be carried out in a usage-dependent and, in particular, preventative manner based on the recorded load and / or consumption data.

[0038] Alternatively or additionally, it can be provided that the numbers determined in step C) are used for machining additional workpieces, in particular for determining their arrangement and / or alignment in the workspace of the machine tool. The additional workpieces can, in particular, be arranged and / or aligned such that areas that are difficult to machine, for example contours that require particularly precise machining, are placed in previously less stressed or worn areas of the workspace. Furthermore, by appropriately arranging and aligning the additional workpieces, the stress on the machine tool can be evenly distributed within the workspace in order to increase the service life of the machine tool.

[0039] The scope of the present invention further includes a machine tool, in particular a laser processing machine, comprising a tool for processing a workpiece, a sensor device for measuring at least one operating parameter during the processing of the workpiece with the tool, and a control device which is designed to carry out a method according to one of the preceding claims.

[0040] The machine tool according to the invention enables the implementation of the above-described manufacturing method according to the invention. The machine tool typically has at least one machine axis for moving the tool relative to the workpiece. The sensor device can comprise one or more sensors. The control device can be arranged locally on the machine tool. Alternatively, the control device can be designed independently of the machine tool and, in particular, can be configured to control multiple machine tools.

[0041] Further features and advantages of the invention will become apparent from the description, the claims, and the drawings. According to the invention, the above-mentioned and further-described features can be used individually or in combination in any convenient way. The embodiments shown and described are not intended to be exhaustive, but rather are exemplary in nature for describing the invention.

[0042] Detailed the and

[0043] The invention is illustrated in the drawing and is explained with reference to

[0044] Examples of implementation are described.

[0045] Fig. 1 shows a machine tool according to the invention in a schematic representation;

[0046] Fig. 2 is a schematic flow diagram of a manufacturing method according to the invention;

[0047] Fig. 3 is an exemplary representation of the course of the path and acceleration of a tool of the machine tool during machining plotted over time;

[0048] Fig. 4 is a schematic representation of event frequencies (numbers) of the values ​​from Fig. 3 divided into multidimensional size classes.

[0049] Figure 1 shows a machine tool 10 according to the invention. The machine tool 10 is, by way of example, a laser processing machine, in particular a laser cutting machine. The machine tool 10 has a tool 12, in this case a laser processing head. During the processing of a workpiece 14, a laser beam (not shown in detail) can exit from a nozzle 16 together with a process gas. The workpiece 14 is arranged on a workpiece support 18 with a plurality of support webs 20. The tool 12 is movable relative to the workpiece 14 along a plurality of machine axes 22, 24.

[0050] The machine tool 10 has a sensor device 26 with a plurality of sensors 28, 30 for detecting operating parameters during the machining of the workpiece 14. One or more sensors 28 can, for example, measure the position, speed, and / or acceleration of the tool 12 along the machine axes 22, 24. One or more sensors 30 can, for example, measure a power output and / or a temperature of the tool 12. It is understood that additional sensors can be provided for measuring other operating parameters.

[0051] The machine tool 10 further comprises a control device 32. The control device 32 is configured to control the machining of the workpiece 14 with the tool 12 and to process the measured values ​​of the sensor device 26.

[0052] Figure 2 shows a schematic flow diagram of the machining of the workpiece 14 with the machine tool 10. In a step 102, the workpiece 14 is machined with the tool 12. Here, the workpiece 14 is cut through by the laser beam.

[0053] During the machining of the workpiece 14, the sensor device measures several operating parameters in steps 104a, 104b, 104c, for example, a position y of the tool 12 along one of the machine axes and the acceleration a of the tool 12 along this machine axis (see Figure 3). The various operating parameters can be measured at a fixed frequency, for example, 1000 Hz. Preferably, all operating parameters are measured at the same times. Another operating parameter can be a period of time over which another operating parameter assumed a specific value. This period of time can correspond to the inverse of the measuring frequency.

[0054] During processing 102, in steps 106a, 106b, and 106c, several stress parameters are calculated from the measured operating parameters. In the simplest case, one stress parameter can correspond to one operating parameter. However, several operating parameters can also be combined with one another in a predefined manner to obtain a stress parameter. Size classes are predefined for the stress parameters. Preferably, a size class is delimited by pairs of values ​​of several stress parameters. In other words, the size classes can be multidimensional. The value pairs can encompass identical or different value ranges (for a respective stress parameter).Different value ranges can, for example, simulate the grid of support webs 20 and the gaps between them in the workpiece support 18, in particular if the stress parameter in question is related to the position of the tool 12 along the machine axis 22 or describes this position.

[0055] Then, during processing 102, in steps 108a, 108b, and 108c, the calculated values ​​of the operating parameters are divided into the predefined size classes. In other words, the number of times the operating parameters assume a value within the different size classes is counted. Figure 4 shows the corresponding numbers n for movements of the tool 12 according to Figure 3 plotted against the underlying operating or stress parameters, here position y and acceleration a. This number is saved for all predefined size classes.

[0056] On the one hand, these numbers can be determined for the machine tool 10 over its entire service life. On the other hand, these numbers can be determined on a machining-related basis, for example, for the machining of one workpiece 14.

[0057] From the workpiece-related quantities, processing-related costs, consumption, and / or wear data can be determined in a step 110. These can then be used for billing or calculation.

[0058] Maintenance measures for the machine tool 10 can be derived from the lifetime-related numbers in a step 112. For example, components of the machine tool 10 can be serviced or replaced if the numbers in the different size classes of the stress parameters meet predefined criteria.

[0059] The lifetime-related numbers can be used particularly advantageously to control the machining of additional workpieces in steps 102'. The additional workpieces can, in particular, be arranged and aligned in the working space of the machine tool 10 such that the loads on the machine tool 10 are distributed evenly. This can, for example, ensure that the machine axes 22, 24 and their drives wear evenly. Alternatively or additionally, the additional workpieces can be arranged and aligned in the working space of the machine tool 10 such that areas of the workpieces that are difficult to machine, for example areas with particularly tight tolerances or high dynamic demands on the machine tool 10, are located in areas of the working space that were previously subject to lower stresses and therefore less wear.

[0060] In summary, the invention relates in particular to a manufacturing method in which stress parameters are recorded in a multidimensional grid and divided into size classes. Event frequencies are determined. In other words, the number of times the stress parameters assume a value within the different size classes is counted. The count can extend over the entire operating period of the machine tool or individual machining operations or partial machining operations. The stress parameters can describe load, wear, and / or consumption variables. The stress parameters can be measured directly or derived from measured operating parameters. By evaluating the determined numbers in the size classes, maintenance measures and / or further machining processes can be controlled.In particular, maintenance measures and / or further machining operations can be performed depending on the determined quantities. The manufacturing method according to the invention enables, in particular, context-related recording and analysis of the machining operations performed with minimal memory requirements, and without the ability to reconstruct the actual machining operations performed from the stored quantities.

[0061]

[0062] Machine tool 10

[0063] Tool 12

[0064] Workpiece 14

[0065] Nozzle 16

[0066] Workpiece support 18

[0067] Support bars 20

[0068] Machine axes 22, 24

[0069] Sensor device 26

[0070] Sensors 28, 30

[0071] Control device 32

[0072] Position y

[0073] Acceleration a

[0074] Number n

[0075] Edit 102, 102'

[0076] Measuring 104a, 104b, 104c of operating parameters

[0077] Calculating 106a, 106b, 106c stress parameters

[0078] Determine 108a, 108b, 108c of numbers for size classes of

[0079] Stress parameters

[0080] Determining 110 of processing-related data

[0081] Carrying out 112 maintenance measures

Claims

Patent claims 1. Manufacturing process in which a workpiece (14) is machined with a machine tool (10), wherein during the machining A) at least one operating parameter of the machine tool (10) is measured, characterized in that several size classes are predefined for at least one stress parameter of the machine tool (10), and that during machining B) from the at least one measured operating parameter, the at least one stress parameter is calculated, and C) a number indicating how often at least one stress parameter lies within each of the size classes is stored.

2. Manufacturing method according to claim 1, characterized in that at least two operating parameters are measured.

3. Manufacturing method according to claim 2, characterized in that the at least one stress parameter is calculated from at least two operating parameters.

4. Manufacturing method according to one of the preceding claims, characterized in that the at least one stress parameter is calculated with the time period over which a respective operating parameter was measured.

5. Manufacturing method according to one of the preceding claims, characterized in that at least two stress parameters are calculated.

6. Manufacturing method according to claim 5, characterized in that the at least two stress parameters are calculated for the same times and assigned to a size class for the multiple stress parameters.

7. Manufacturing method according to one of the preceding claims, characterized in that steps B) and C) and preferably also A) are carried out at a fixed frequency.

8. Manufacturing method according to one of the preceding claims, characterized in that the size classes for the at least one stress parameter each comprise the same range of values.

9. Manufacturing method according to one of the preceding claims, characterized in that the size classes for the at least one stress parameter comprise different ranges of values, in particular wherein size classes with larger and smaller ranges of values ​​alternate with one another.

10. Manufacturing method according to one of the preceding claims, characterized in that step C) is carried out over a period of use of the machine tool (10).

11. Manufacturing method according to one of the preceding claims, characterized in that step C) is carried out again for a further raw part, a further workpiece (14) or a further machined contour.

12. Manufacturing method according to one of the preceding claims, characterized in that the machine tool (10) is a Laser processing machine, in particular where a laser cutting process or a laser welding process takes place. Manufacturing method according to one of the preceding claims, characterized in that the at least one operating parameter is selected from - Position (y), in particular of a tool (12) of the machine tool (10), in particular along a machine axis (22, 24) of the machine tool (10), - Acceleration (a), in particular of the tool (12), in particular along the machine axis (22, 24), - Current consumption, force and / or torque of a drive, especially of the machine axis, - Machining force of the tool (12) of the machine tool (10), - Power output of the tool (12) of the machine tool (10), in particular laser power of a laser processing head, - Pressure and / or volume flow rate of a process gas, - Time increment over which another operating parameter assumes a specific value, - Temperature, in particular of a tool (12) of the machine tool (10), and / or - Stray light. Manufacturing method according to one of the preceding claims, characterized in that maintenance, repair and / or replacement of at least one component of the machine tool (10) is carried out when the numbers determined in step C) meet a predefined criterion. Manufacturing method according to one of the preceding claims, characterized in that the numbers determined in step C) are used for machining further workpieces (14), in particular for determining their arrangement and / or orientation in the working area of ​​the machine tool (10) will be used. Machine tool (10), in particular laser processing machine, with - a tool (12) for machining a workpiece (14), - a sensor device (26) for measuring at least one operating parameter during the machining of the workpiece (14) with the tool (12), and - a control device (32) configured to carry out a procedure according to any of the preceding claims.

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