Method for offline and / or online identification of a state of a machine tool, of at least one machine tool tool or of at least one workpiece machined in a machine tool

Abstract

The present invention relates to a method (100) for offline and / or online identification of the state of a machine tool (WM), at least one of its tools (WZ) or at least one workpiece (WS) being machined therein, wherein the machine tool (WM) has sensors that enable the detection of the position of the tool and / or tool holder in a manner that is at least spatially and temporally resolved, comprising the steps of: a) detecting or providing (102) the position P of the tool and / or tool holder (WH1, WH2) at a series of time points i, i = 1...n; b) determining (104) a series of position changes Δm for the series of time points i according to formula (I); i b2) Determine a series of velocity changes Δv according to formula (II) which has formulas (III) and (IV). i c) Based on the position change Δm i and velocity change Δv i Identify the state of the tool (WZ) (c1), the state of the tool holder (WH1, WH2) (c2), the state of the machine tool (WM) (c3), and the state of at least one workpiece (WS) being machined in the machine tool (WM) (c4).

Description

TECHNICAL FIELD

[0001] The present application relates to a method for identifying the state of a machine tool, at least one tool thereof or at least one workpiece machined therein, offline and / or online, wherein the machine tool has at least one, preferably rotatable, clamping device for clamping a workpiece to be machined and at least one movable tool holder for positioning a tool held therein, with which the workpiece can be machined, and sensors with which the position of the tool and / or the tool holder can be detected at least in a spatially and temporally resolved manner. BACKGROUND

[0002] Machine tools, for example numerical control machine tools, are now equipped with a large number of sensors, which can continuously record various operating parameters. The time series of operating parameters thus obtained can enable an analysis of the operating state of the machine tool. It is known from WO 2020 / 038815 Al, for example, to determine the state of the device using a trained support vector machine. Here, the operating parameter space is subdivided into classification volumes, at least one of which identifies a normal state of the device and at least one further classification volume identifies a fault state of the device.

[0003] The disadvantage is that, for the application, on the one hand a neural network is required and on the other hand a large amount of training data, so that a complex method is provided in the prior art.

[0004] Furthermore, with the known methods it is difficult to determine different normal operating states of the machine tool. A normal operating state is an operating state in which the machine tool performs the predetermined, i.e. programmed, method steps without error as prescribed. The normal operating state of the machine tool essentially includes the main states of the cutting process and the secondary states, for example the movement of the tool holder during a return stroke, a tool change, a standstill time or a simple idling.

[0005] The feasibility of currently available methods for deriving and detailed analysis of unprofitable non-productive times is therefore limited. Furthermore, individual sequences of one of the elements cannot be identified unambiguously or without error. Elements of the machine tool are understood to mean the constituent parts of the machine tool which can be moved in the machine tool. The term "element" is therefore a collective term in the present application, which can be understood in detail as one or more tools, their tool holders and the clamping device for clamping the workpiece.

[0006] While the operating and standstill of the machine tool is distinguished when checking the operating state from internal machine signals. This is achieved by the power consumption of the drive motor and the changed position data of the tool holder or tool. However, the non-productive times have so far only been estimated or recorded manually on the machine. In order to describe the operating state in detail and completely, a continuous recording of all events is required. SUMMARY

[0007] In this respect, it is an object of the present application to provide a method for identifying a state or a sequence of a machine tool, for example a CNC machine tool, offline and / or online, with which a running state or a sequence can be identified in a simple and effective manner. At the same time, it is an object of the present application to give a device corresponding thereto.

[0008] According to the present application, a running state of a machine tool or a sequence of movements of at least one tool thereof or at least one workpiece machined therein can be identified. The machine tool has at least one, preferably rotatable, clamping device for clamping a workpiece to be machined and at least one movable tool holder for positioning a tool held in the clamping device with which the workpiece can be machined, and a sensor with which the position of the tool and / or the tool holder can be detected at least in a spatially and temporally resolved manner. In order to carry out the identification according to the present application, the following steps are carried out.

[0009] First, at a series of consecutive time points i, with i = 1... n, the position P of the tool and / or the tool holder is detected by the sensor in a spatially and temporally resolved manner. According to steps b) and c), the time series of these data can be evaluated immediately after detection, i.e. online. It is also possible to analyze already completed running phases of the machine tool according to steps b) and c) using the method according to the present application. In this case, the historical data recorded during these running phases are used for the evaluation method described here retrospectively, i.e. offline.

[0010] The data present at the time points i as a time series of the sensor relative to the tool and / or the tool holder are respectively

[0011] In a first calculation step, according to

[0012]

[0013] are converted into a series of position changes Am i and

[0014] According to and

[0015] and Equations (3) and (4) are converted into a series of velocity changes Av i .

[0016] From these data series, a state of the tool, the tool holder, the machine tool and / or a workpiece machined in the machine tool can then be derived.

[0017] The particularity of the method described lies in its simplicity, neither complex transformations of the derived or provided sensor data nor the training of any always designed neural network is necessary.

[0018] According to a particularly preferred design of this method, the position P is detected and stored as coordinates P in a Cartesian coordinate system. i (x i y i , z i Furthermore, it can be used for evaluation methods. Therefore, based on the x, y, and z axes of the coordinate system, the position change Δm can be calculated. i Determine their corresponding components Δm xi , Δm yi , Δm zi The sum is the velocity change Δv i Determine their corresponding components Δv xi Δv yi Δv zi Such methods are always based on the coordinate system used by the machine tool, thus eliminating the need to adjust sensor data detected from the machine tool. This supports real-time determination of the operating status and simplifies the implementation of the method.

[0019] The identified states are particularly preferably operating states, especially normal operating states, which represent the movement of the tool or tool holder, particularly for workpiece machining, for tool repositioning, particularly return, for tool change; and the stationary phases of the tool or tool holder, particularly downtime and / or idling, and / or deviations from the preset movement speed of the clamping device, particularly overrun commands. Furthermore, this method allows for the division of each operating state into multiple sequences with different meanings when travel is involved. This specifically means that the "cutting process" state is divided into sequences of "approach," "cutting" in the sense of "tool reaching and contacting the workpiece," "cutting sequence" in the sense of "tool machining the workpiece," and "cutting" in the sense of "tool losing contact with the workpiece." This also applies to other travel and movement of the component.

[0020] Advantageously, additional sensors detect the electrical parameters of the machine tool's drive motor. For example, additional sensors detect the power consumption of the drive motor and / or the existing supply voltage, by means of, for example, rotating the clamping device and / or moving the tool holder in space. The resulting characteristic curves and / or time series can then be analyzed in further method steps. For example, these characteristic curves or time series are combined with a previously derived series of position and speed changes, making analysis, particularly of the cutting process, feasible. Faulty operating conditions can also be determined. On the one hand, these findings can protect the machine tool from indirect damage. On the other hand, workpiece damage can be identified and reported for timely inspection of workpieces not yet completed. This avoids unnecessary further processing of workpieces that may no longer be usable, improving machine tool utilization, saving costs, and accelerating the completion of a series of workpieces.

[0021] Further data, in particular correction factors or tool parameters, are advantageously provided in advance for deriving the state. For example, the correction factors are values for determining the exact position of the cutting edge of the tool.

[0022] In an advantageous method step, a series of position changes and / or a series of velocity changes are analyzed in terms of boundary value considerations. For example, the formula

[0023]

[0024] It is derived whether a tool change or a cutting process is present, wherein U is a matrix describing the position of the tool or tool holder.

[0025] If a case distinction is made, a simple and effective type of state recognition is given, in which it is checked whether the correlation of the position change Am i and / or the velocity change Av i or one or more components thereof is less than 1, equal to 1, greater than or equal to 1 or 0.

[0026] The series of position changes and / or velocity changes are advantageously represented as characteristic curves in a diagram and / or are provided in a data array, from which the analysis of the respective state is carried out.

[0027] It is particularly advantageous to use a method for recognizing an overload of one of the machine tool drives, for recognizing wear of the machine tool and / or the tool, for recognizing a manufacturing fault or a workpiece fault and / or for recognizing a process instability, in particular a chatter, i.e. a regenerative effect.

[0028] The above-mentioned method or preferred design solutions thereof are advantageously implemented by a computer. The present application therefore also comprises an apparatus for data processing, which comprises means for carrying out the method or for carrying out the preferred design solutions. Furthermore, the present application also comprises a computer program product, which comprises instructions, which, when the program is executed by a computer, cause the computer to carry out the steps of the method or of the preferred design solutions. The present application also comprises a computer-readable medium, which contains instructions, which, when executed by a computer, cause the computer to carry out the steps of the method or of the preferred design solutions.

[0029] The description of the preferred design solutions of the present application given so far contains a number of features, which are partly combined in various embodiments in a plurality of groups. However, the features can also be considered individually and combined into more meaningful combinations. In particular, each of the features can be combined individually and in any suitable combination with the method according to the present application, the apparatus for data processing according to the present application and the computer-readable medium according to the present application. Furthermore, the method features can also be considered as attributes of the respective apparatus units.

[0030] The above-mentioned characteristics, features and advantages of the application as well as the way and method of realizing them are explained in more detail in accordance with the following description of embodiments in conjunction with the drawings. The embodiments serve to explain the application and do not restrict the application to the combinations of features specified therein, even not in relation to the functional features. Furthermore, the features suitable therefor of each embodiment can also be considered explicitly isolated, removed from one embodiment, introduced into another embodiment to complement it. BRIEF DESCRIPTION OF DRAWINGS

[0031] In the drawings:

[0032] Figure 1 A machine tool is shown in a schematic view,

[0033] Figure 2 A diagram is shown Figure 1 The working space of the machine tool shown,

[0034] Figure 3 A flow chart of a method for identifying a machine tool state is shown,

[0035] Figure 4 A diagram of a cutting process is shown,

[0036] Figure 5 A matrix U with a series of position changes is shown,

[0037] Figure 6 A characteristic curve of the z-axis torque forming current for the entire machining process of a workpiece is shown,

[0038] Figure 7 A characteristic curve of the drive torque of a single machining spindle is shown. DETAILED DESCRIPTION

[0039] In all drawings, identical features have identical reference signs.

[0040] Figure 1 A turn-milling CNC machine tool CM is shown exemplarily as machine tool WM. The machine tool WM comprises a working space AR, which is closable by a sliding door TR, in which two opposing spindles SP, a main spindle SP1 and a counter spindle SP2, are arranged as clamping devices AV, AV for clamping a workpiece WS to be machined (not shown here). Figure 2 Furthermore, two movable tool holders WH1, WH2 are provided within the working space AR, which tool holders can each accommodate a plurality of tools (not shown here). The machine tool WM further comprises a control system BE for programming, controlling and monitoring its elements.

[0041] Subsequently in Figure 2The work space AR and the elements arranged therein are shown in detail. The two spindles SP1 and SP2 are arranged concentrically to one another and are rotatable about their common longitudinal axis. They also each comprise a chucking device AV by means of which a workpiece WS to be machined can be rotated. The machine tool WM also has two tool holders WH1 and WH2 which are capable of spatial displacement in all three spatial directions. The upper tool holder WH1 comprises only three stations as an electric milling spindle, while the tool holder WH2 arranged below is designed as a tool turret having a plurality of stations.

[0042] For the detection of positions, the control system BE of the machine tool WM uses a virtual Cartesian coordinate system KS having three mutually orthogonal machine tool axes x, y and z. The two spindles SP1 and SP2 and the chucking devices AV arranged thereon are rotatable about the z axis and movable along the z axis, so that a workpiece can be transferred from the sub-spindle to the main spindle and vice versa without the support of a user.

[0043] The tool magazine space MG, which is closed by a tool magazine door in the illustrated representation, adjoins the work space AR. In the tool magazine space MG, a large number of tools WZ, i.e. drills, milling cutters, etc., are arranged so as to be able to be gripped by the upper tool holder WH1 when the tool magazine door is opened and to be able to be put back or returned into the tool magazine space.

[0044] The machine tool WM can be in different states, i.e. operating states, during its operation. Here, a distinction must be made between, on the one hand, faulty operating states and, on the other hand, compliant operating states, i.e. so-called normal operating states. One example of a faulty operating state is the "tool damage" state. Other operating states which indicate a fault can be considered. On the other hand, a compliant operating state can represent, for example, a "cutting process", an "idling", an "override command" or a "tool change". An override command is understood to be a manual intervention by a user into the machine tool WM which accelerates or delays a programmed sequence of workpiece machining. Other compliant operating states can also be sequences of the above-mentioned operating states, if their sub-sections are recognized to some extent. The machining of the workpiece WS can then be analyzed and, or optimized by means of the operating states recognized by the method.

[0045] The workpiece can also be in different states. With reference to the workpiece WS, for example, a possible manufacturing fault can be recognized in a spatially resolved manner by means of the method in order to reduce the outlay for quality assurance.

[0046] To derive the state, the machine tool WM is equipped with a large number of not shown sensors. With some of these sensors, the position of the tool and / or the tool holder and the clamping device can be derived in a spatially and temporally resolved manner. The position, i.e. the spatial coordinates P(x, y, z), of the clamping device AV or of the workpiece WS clamped therein, of the tool WZ or of the tool holder WH1, WH2 is usually detected individually for each machine axis by the respective sensor.

[0047] Furthermore, for example, the position of the cutting edge of the tool WZ can be determined via the position of the tool holder, the previously provided data on the dimensions of the associated tool being supplemented therewith. The position of the tool cutting edge in the machine tool WM can also be measured automatically to derive correction data. Other sensors can continuously detect the current of the drive motors (not shown) of the machine tool and the supply voltage with which the respective rotatable and / or movable elements can be driven, i.e. rotated and / or repositioned.

[0048] In this respect, the signals of these sensors contain data, for example, which can be detected during machine standstill, tool change, idle run, rapid movement, acceleration effects, cutting sequences and the actual cutting process. The recorded data signals thus also represent position data, drive parameters and power, correction factors or tool parameters.

[0049] Figure 3 The method proposed for the recognition of the state is shown schematically in Fig. 1, wherein the following further terms are defined which characterize the requirements:

[0050] The feed speed of an element is calculated from the product of the current feed f along the machine axis considered and the associated rotational speed n, which is shown exemplarily below only for the x-axis:

[0051] v f,x = f x *n (1)

[0052] For the position change of the element considered required for the state recognition, the vector Am is introduced, by which the ratio, i.e. the quotient, of the position at any point in time i and its previous position, i.e. the position at point in time i-1, is defined. This is shown exemplarily in equation 2 for the x-coordinate of the element concerned.

[0053]

[0054] The method offers the possibility of being able to use the method offline and online. Furthermore, for example, a change in the feed speed in the x-direction is applicable to the relationship shown in equation 3:

[0055]

[0056] wherein the speed is derived according to the following equation

[0057] and (4), (5). In the first method step 102 of the method 100 according to the application, the respective current position of the tool WZ and / or of the tool holders WH1, WH2 is recorded or provided as data at a series of time points. According to the above equations (1) - (5), the processing of this data in the second method step 104 can be realized immediately at the time of its generation, which enables an online recognition of the state. In the case of a detection of data for the calculation and state recognition temporally offset from the data detection, the offline recognition of the state is considered. In the last method step 110, then, the state of the tool, of the tool holder, of the machine tool and / or of the workpiece being machined in the machine tool is recognized from the previously derived or provided position changes and speed changes.

[0058] In principle, for the position changes and speed changes, a distinction can be made between different cases for each machine axis and for each element. Here, it is first only necessary to derive in which direction the element is moved. This can be derived with the aid of the following table 1. The change in position and the change in speed represent only the quotient of the raw data.

[0059] Table 1: Meaning based on the quotient

[0060]

[0061]

[0062] Then, from a comprehensive consideration of two or more cases, the state, in particular the operating state, of the machine tool at the observed time point of the series of time points can be derived.

[0063] In the following, a number of conditions are listed by way of example, according to which the method can recognize different operating states.

[0064] a) Return recognition:

[0065] If several cutting processes are carried out on one workpiece, the tool must return to the starting point. To recognize this state, one of the following three conditions must be met:

[0066] Δm z >1 & Δm x >1

[0067] Δm z =1 & Δm x >1

[0068] Δm z >1 & Δm x =1

[0069] b) Identification of standstill and idle running: If the machine tool is set to idle running manually by the user during machining, for example, so that no machining takes place although the spindle is rotating, the following conditions apply. This also applies to the standstill of the spindle

[0070] Δv f,x = Δv f,z = Δv f,y = 0

[0071] c) Identification of idle running or standstill:

[0072] Idle running can be distinguished from standstill by means of the spindle speed additionally read from the control system BE. If the speed of the clamping device AV, which holds the workpiece WS, is not equal to 0, there is idle running.

[0073] d) Identification of override command:

[0074] The control system BE of the machine tool returns a manually executed override command. This override command can be read and then processed. If the conditions from Figure 4 apply, it is assigned to the cutting process. The override command does not change the conditions from Figure 4 It should be noted that depending on the command, the conditions for identifying standstill and idle running can also apply.

[0075] e) Identification of the actual cutting process and derivation of individual cutting sequences:

[0076] In order to identify individual cutting sequences in continuous machining, the signal of the feed speed of the axes is considered in a first step. In order to ensure that even low feed speeds are identified during machining, it is possible to square the value and then round it to the nearest natural number, including 0.

[0077] In a next step, the position change of the respective axis and the change in feed speed are determined with high precision. This leads to the fact that small deviations can be identified.

[0078] It is then necessary to perform a further case differentiation in order to be able to identify the cutting sequence that is currently being executed. The possible cases and the respective conditions are shown in Figure 4 The prescribed conditions also apply to plunge turning and internal machining of the workpiece.

[0079] In the embodiment shown in Figure 4 , for example, the first tool holder WH1 is moved in the negative z direction from its rest position. This state can be identified by means of the specified quotient. For this purpose, all the conditions mentioned in B1 must be met:

[0080] Δv f,x = 1

[0081] Δv f,z= 1

[0082] Am x = 1

[0083] Am z <1

[0084] With the passage of time, the tool holder WH1 is also moved in the positive X direction, thus satisfying all conditions B2. With the first occurrence of sensor data satisfying condition B4, the method recognizes the start of a cutting process: a cutting sequence. When condition B4 is no longer satisfied but condition B5 is, then the end of the cutting process (cutting sequence) is recognized.

[0085] To implement the method according to the invention, for each element of each machine axis, data points of the original signal that are suitable for the respective case are stored in a matrix U, as shown exemplarily in Figure 5 for one element of one axis. In the shown embodiment, for seventeen time points from a series of time points, seventeen quotients are shown that are attributed. The quotient is preferably the feed speed in the negative z direction.

[0086] If only further analysis of the cutting process is required after the selection of the operating state, this case is recognized and eliminated at tool change, since some of the conditions can also apply to tool change.

[0087] In the method according to the invention, tool changes can be recognized by considering a boundary value. The boundary value is defined as the sum of the empirically averaged value of the feed speed (U v，f (i)) stored in U and the standard deviation of 50%:

[0088]

[0089] Once the data point of the feed speed in the matrix U exceeds the boundary value, this data point is recognized as belonging to a tool change and is set to zero in the matrix U. The indices of the values of the matrix U that are not recognized as tool changes thus belong to a cutting process and are written in the vector t in the next step to select the cutting process. The vector t thus contains only those time points for which the feed speed in the negative z direction is not equal to 0. By shifting to the vector t, the distances (d) between the individual measurement points can be determined:

[0090]

[0091] This determines the values stored in d. For coherent measurement signals, d = 1. Thus, by the condition b = e + 1, the starting value (b) of the subsequent cutting process of the individual separate cutting process and the end value (e) of the current cutting process can be derived, which values cannot be immediately recognized as such in the shown matrix U.

[0092] In addition, the temporal changes in the position change and the speed change can also be quantitatively evaluated and conclusions can be drawn about the operating state over a freely selectable or predetermined time range. For example, a change in the speed change in the form of a pulse over the time range considered can indicate a regenerative effect. By means of this method, it is also possible to identify differences in the speed change that occur during the same processing step of two identical workpieces that are manufactured one after the other. An indication of the wear of the tool used during this time can thus be drawn.

[0093] In addition, further internal machine signals can be detected in a further method step 106 Figure 3 ) in particular current and voltage signals for the drive motor of the machine tool. Here, Figure 6 The torque-forming current of the drive motor responsible for the adjustment along the z-axis throughout the machining of the workpiece is shown. This includes the individual processing time BZ and the accumulated non-productive time NZ.

[0094] Figure 7 A section DL from the diagram according to Figure 6 is shown with a higher temporal resolution. The current change for driving the spindle is shown over time and can be divided into a plurality of time sections in chronological order. During a first time section K1 between the time point t0 to the time point t1, the drive is in a standstill state. Then a needle-shaped current pulse occurs at the time point 1 as a time section K2, followed by a time section K3 for motor drive regulation during which the spindle is moved to the programmed position. There, at the time point 2, a time section K4 begins in which the tool WZ reaches the workpiece WS and contact is made. This is a sequence section. The time section K4 is also relatively short and ends at the time point t3, followed by a time section K5 for the main machining of the workpiece, i.e. the cutting process. This ends at the time point t4. Then, between the time points t4 and t5, a second drive regulation K3 is again implemented and between t5 and t6 a second acceleration effect K2.

[0095] Therefore, in a further method step 106 Figure 3 , such machine signals can be recorded or provided and taken into account in the state recognition in the method step 110. This opens up the possibility of recognizing unprofitable process states, such as standstill, idling, tool change, rapid movement or the described override command. In particular, taking into account further machine signals makes it possible to recognize a fault state, for example if the current changes unexpectedly Figure 7 , arrow PF. This allows the manufacturing process to be adjusted as required.

[0096] Overall, it is possible to identify and draw conclusions about individual cutting processes from a continuous manufacturing process. In addition, the process represents a simple and low-cost method for online / offline process monitoring throughout the manufacturing process.

[0097] Although the application has been illustrated and described in detail by preferred embodiments, the application is not limited to disclosed examples and other variations can be derived therefrom without departing from the scope of the application.

Claims

1. A method (100) for identifying a running state, which running state pertains to a machine tool (WM), in an offline and / or online manner, wherein the machine tool (WM) having at least one clamping device (AV) for clamping a workpiece (WS) to be machined; and at least one movable tool holder (WH1, WH2) for positioning a tool (WZ) held in the tool holder, with which tool the workpiece (WS) can be machined; and a sensor with which a position of the tool and / or the tool holder can be detected at least in a spatially and temporally resolved manner, the method comprising the following steps: a) detecting or providing (102) a position P of the tool and / or of the tool holder (WH1, WH2) at a series of time points i, i = 1... n, wherein the position P is present as coordinates P i (x i , y i , z i ) of a Cartesian coordinate system (KS), b) for the series of time points i According to derived (104) b1 ) a series of position changes Am of the tool (WM), of the tool holder (WH1, WH2), and / or of the clamping device (AV) i and according to and and deriving a sequence of speed changes Δv of the tool (WM), of the tool holder (WH1, WH2), and / or of the clamping device (AV) i wherein in terms of the x, y, z axes of the coordinate system (KS), for the position change Δm i determining a respective component Δm xi , Δm yi , Δm zi and for said speed variation Δv i determining a respective component Δv xi , Δv yi , Δv zi , c) depending on the position change Am i and the speed change Av i identifying (110) the operating state of the tool (WZ), wherein the running state representing a movement of the tool and / or the tool holder, a standstill phase of the tool and / or the tool holder, and / or a deviation from a preset movement speed of the clamping device.

2. The method (100) of claim 1, wherein The clamping device is rotatable.

3. The method (100) according to claim 1, wherein the running state representing d) a movement of the tool and / or the tool holder, d1) for workpiece machining, d2) for tool repositioning, d3) for tool change, wherein e) the running state representing a downtime, and / or an idling, and / or f) a deviation from an override command.

4. The method (100) of claim 3, wherein The running state also represents d) a movement of the tool and / or the tool holder, d1) for a cutting sequence of a workpiece, d2) for a return of a tool.

5. The method (100) according to any one of claims 1 to 4, wherein A further sensor detects an electrical parameter of a drive motor of the machine tool.

6. The method (100) according to any one of claims 1 to 4, wherein Further data for deriving a state are provided in advance and / or derived and used during the identification.

7. The method (100) of claim 6, wherein The further data for deriving a state are correction factors or tool parameters.

8. The method (100) according to any one of claims 1 to 4, wherein According to the boundary value consideration to analyze a series of said position changes Δm i and / or said speed changes Δv i .

9. The method (100) according to any one of claims 1 to 4, wherein, The recognition of the state takes place differently depending on the case, wherein it is checked whether the values involved are used for a change in position Δm i and / or a change in speed Δv i or, if according to claim 3, one of the components of the change in position Δm i and / or the change in speed Δv i is less than 1, equal to 1, greater than 1 or 0.

10. The method (100) according to any one of claims 1 to 4, wherein a series of position changes Δm i and / or speed changes Δv i are represented in a diagram as a characteristic curve or provided in a data array and are dependent on the position changes Δm i and / or the speed changes Δv i An analysis of the respective states is effected.

11. The method (100) according to any one of claims 1 to 4, for g) identifying an overload of one of the drives of the machine tool, h) identifying a wear of the machine tool and / or the tool, i) identifying a manufacturing fault or a workpiece fault, and / or j) identifying a process instability.

12. The method (100) according to claim 11, for identifying a chatter in a process.

13. The method (100) according to any one of claims 1 to 4, which method is computer-implemented.

14. An apparatus for data processing, comprising means for carrying out the method according to any one of claims 1 to 13.

15. The apparatus for data processing of claim 14, wherein, The apparatus is a control system (BE).

16. A computer program product comprising instructions which, when the program is executed by a computer, cause the computer to carry out the steps of the method according to any one of claims 1 to 13.

17. A computer-readable medium comprising instructions which, when executed by a computer, cause the computer to carry out the steps of the method of any one of claims 1 to 13.

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