METHOD AND DEVICE FOR QUALITY ASSESSMENT OF A PROCESSING OPERATION

Abstract

In a method and device for assessing the quality of a processing operation, a workpiece with specific processing parameters is processed along a processing trajectory. The (X), wherein the processing result is measured by at least one sensor and at least one sensor signal is recorded and at least one quality parameter is determined based on at least one sensor signal and the at least one quality parameter is compared with quality parameter threshold values to assess the quality of the processing result. During the assessment of the processing operation quality, changes made to the processing parameters from target values during the processing are automatically taken into consideration, in that, instead of the quality parameter threshold values, quality parameter threshold values adapted to the changes in the processing parameters are determined, and the at least one quality parameter for assessing the quality of the processing result is compared with the adapted quality parameter threshold values.

Claims

1. A method for assessing the quality of a processing operation, in which a workpiece (W) with specific processing parameters (P.sub.i(x)) is processed along a processing trajectory (X), wherein the processing result (R(x)) of the processing operation along the processing trajectory (X) is measured by means of at least one sensor (2) and at least one sensor signal (S.sub.j(x)) is recorded and at least one quality parameter (Q.sub.k(x)) is determined on the basis of at least one sensor signal (S.sub.j(x)) and the at least one quality parameter (Q.sub.k(x)) is compared with quality parameter threshold values (Q.sub.k,o(x), Q.sub.k,u(x)) in order to assess the quality of the processing result (R(x)) of the processing operation, wherein, during the assessment of the quality of the processing operation, changes made to the processing parameters (ΔP.sub.i(x)) from the target values of the processing parameters (P.sub.i,soll(x)) during the processing of the workpiece (W) along the processing trajectory (X) are automatically taken into consideration, in that, instead of the quality parameter threshold values (Q.sub.k,o(x), (Q.sub.k,u(x)), quality parameter threshold values (Q.sub.k,o(x), (Q.sub.k,u(x))) adapted to the changes in the processing parameters (ΔP.sub.i(x)) are determined, and the at least one quality parameter (Q.sub.k(x)) for assessing the quality of the processing result (R(x)) of the processing operation along the processing trajectory (X) is compared with the adapted quality parameter threshold values (Q.sub.k,o(x), (Q.sub.k,u(x)).

2. The method according to claim 1, wherein the changes made to the processing parameters (ΔP.sub.i(x)) are determined from the target values during the processing of the workpiece (W) along the processing trajectory (X) by comparing the transmitted actual values of the processing parameters (P.sub.i/ist(x)) and transmitted target values of the processing parameters (P.sub.i/soll(x)).

3. The method according to claim 1, wherein the changes made to the processing parameters (ΔP.sub.i(x)) from the target values of the processing parameters (P.sub.i/soll(x)) and/or transmitted actual values of the processing parameters (P.sub.i/ist(x)) and/or transmitted target values of the processing parameters (P.sub.i/soll(x)) are recorded during the processing of the workpiece (W) along the processing trajectory (X) and are subsequently used for automatic consideration in the assessment of the quality of the processing operation along the processing trajectory (X).

4. The method according to claim 1, wherein the quality parameter threshold values (Q′.sub.k,o(x), (Q′.sub.k,u(x)) adapted to the changes in the processing parameters (ΔP.sub.i(x)) are determined from stored quality parameter threshold values (Q.sub.k,o,g(x), (Q.sub.k,u,g(x)) for specific processing parameters (P.sub.i(x)).

5. The method according to claim 4, wherein the stored quality parameter threshold values (Q.sub.k,o,g(x), (Q.sub.k,u,g(X)) are determined from test processing operations for specific processing parameters (P.sub.i(x)).

6. The method according to claim 4, wherein the quality parameter threshold values (Q′.sub.k,o(x), (Q′.sub.k,u(x)) adapted to the changes in the processing parameters (ΔP.sub.i(x)) are determined by interpolation of the stored quality parameter threshold values (Q.sub.k,o,g(x), (Q.sub.k,u,g(x)) for specific processing parameters (P.sub.i(x)).

7. The method according to claim 1, wherein when determining at least one quality parameter (Q.sub.k(x)) from at least one sensor signal (S.sub.j(x)) the change in at least one processing parameter (ΔP.sub.i(x)) is taken into consideration.

8. The method according to claim 1, wherein additional environmental parameters (UP.sub.i, UP.sub.i(x)), such as, for example, a workpiece temperature, an ambient temperature, an air humidity, or the like, are taken into consideration in the assessment of the quality of the processing operation.

9. The method according to claim 1, wherein the processing result R(x) along the processing trajectory (X) can be measured with the aid of the workpiece (W) non-destructive measuring methods, for example with optical sensors (3) as the at least one sensor (2), in particular laser scanners, cameras (4) or the like, X-ray sensors (5), and/or temperature sensors (6), and at least one sensor signal (S.sub.j(x)) can be recorded.

10. The method according to claim 1, wherein the processing result R(x) along the processing trajectory (X) is measured with the aid of measurement methods which destroy the workpiece (W), for example by making cuts through the workpiece (W) at various points along the processing trajectory (X) and making images of the surface of the cuts, using at least one sensor (2), and at least one sensor signal (S.sub.j(x)) is recorded.

11. The method according to claim 1, wherein the processing result R(x) is measured along the processing trajectory (X) during the processing of the workpiece (W) with the at least one sensor (2), the speed of the measurement of the processing trajectory (X) preferably corresponding to the processing speed.

12. The method according to claim 1, wherein the processing result R(x) is measured along the processing trajectory (X) after completion of the processing of the workpiece (W) with the at least one sensor (2), wherein the speed of the measurement of the processing trajectory (X) is preferably greater than the processing speed.

13. The method according to claim 1, wherein if at least one quality parameter (Q.sup.k(x)) is exceeded above a quality parameter threshold value (Q.sub.k,o(x), Q.sub.k,u(x)) or adapted quality parameter threshold value (Q′.sub.k,o(x), (Q′.sub.k,u(x)), a warning is output and/or the excess is stored.

14. The method according to claim 1, wherein, in the case of a weld seam as processing trajectory (X), the processing parameters (P.sub.i(x)) of the welding process welding current (I(x)), welding voltage (U(x)), conveying speed (v.sub.d(x)) of a welding wire (7), setting angle (α(x)) of a welding torch (8) with respect to the workpiece (W), relative position of a welding torch (8) with respect to the workpiece (W) and/or the welding speed (v.sub.s(x)) are taken into consideration.

15. A device (1) for assessing the quality of a processing operation of a workpiece (W) with specific processing parameters (P.sub.i(x)) along a processing trajectory (X), which is designed to carry out the method according to claim 1.

Description

[0028] The present invention is further explained with reference to the appended drawings. In the drawings:

[0029] FIG. 1 shows a schematic processing operation in which a workpiece having specific processing parameters is processed along a processing trajectory;

[0030] FIGS. 2A to 2D schematically outline a method for assessing the quality of a processing operation with various sensors for measuring the processing result along the processing trajectory;

[0031] FIG. 3 shows a schematic representation of the method according to the invention for assessing the quality of a processing operation on a workpiece; and

[0032] FIG. 4 is an example of a deliberate change in the processing parameters during a processing operation and its consideration in the quality assessment of the processing operation.

[0033] FIG. 1 shows a schematic processing operation in which a workpiece W having specific processing parameters P.sub.i(x) is machined along a processing trajectory X to form a processing result R(x). The processing device 10 contains a processing robot 11, which carries the respective processing head 12, with which the workpiece W is processed, and leads along the processing trajectory X to the formation of the processing result R(x). For processing the workpiece W, specific target values of the processing parameters P.sub.i,soll(x) are selected from a plurality of possible processing parameters P.sub.i(x), which are stored, for example, in a database or a memory 9, with which the workpiece W is processed in order to achieve a desired processing result. A manual intervention on the processing device 10 or also an automatic machine intervention in adaptive processing operations (symbolized by the dash-dotted line) can result in changes in the target values of the processing parameters P.sub.i,soll(x) and thus in desired or necessary changes in the processing parameters ΔP.sub.i(x) during the processing operation. In the case of subsequent quality monitoring of the processing result R(x) of the processing operation by appropriate inspection of the processed workpiece W along the processing trajectory X, such changes in the processing parameters ΔP.sub.i(x) are usually not automatically taken into consideration from the target values of the processing parameters P.sub.i,soll(x) in known methods, as a result of which incorrect assessments of the quality of the workpieces W can occur. Due to the fact that conventional quality control systems fail when the processing parameters ΔP.sub.i(x) are deliberately changed, because the changed processing result R′(x) does not correspond to the expected processing result R(x), it is usually necessary to perform a complicated manual check of the workpieces W machined with the deliberately changed processing parameters ΔP.sub.i(x).

[0034] The processing device 10 may be, for example, a welding device for carrying out a joining process on a workpiece W. In this case, a welding torch is fastened to a welding robot, by means of which two or more workpieces W can be joined to one another or a layer can be applied to a workpiece W. The processing result R(x) in this case is a weld seam between two or more workpieces W to be joined or a weld bead on the surface of a workpiece W. Furthermore, the processing device 10 can also be formed by a device for treating the surface of a workpiece W with a plasma torch, a painting device and much more. Depending on the processing operation, the processing result R(x) along the processing trajectory X and also the assessment of the quality of the processing operation and of the respective processing result R(x) along the processing trajectory X differ.

[0035] FIGS. 2A to 2D schematically show a method for assessing the quality of a processing operation with various sensors 2 for measuring the respective processing result R(x) of the processing operation along the processing trajectory X on the basis of a welding process as a processing operation.

[0036] FIG. 2A shows a quality assessment of the processing operation which takes place during or immediately after the processing of the workpiece W (so-called “online” quality assessment). Accordingly, the sensors 2 for measuring the processing result R(x) of the processing operation are arranged along the processing trajectory X of the workpiece W at or behind the processing head 12, so that the processing result R(x) can be measured along the processing trajectory X immediately after the processing operation. The processing head 12 may be, for example, a welding torch 8, via which a consumable welding wire 7 is fed to the workpiece W for carrying out a joining process or build-up welding process. Between the end of the welding wire 7 and the workpiece W, an arc LB burns, which melts the welding wire 7 and the workpiece W. Possible sensors 2 for measuring the processing result R(x) along the processing trajectory X of the workpiece W are, for example, optical sensors 3, cameras 4, X-ray sensors 5 or temperature sensors 6, which measure the processing result R(x) along the processing trajectory X and provide corresponding sensor signals S.sub.j(x) as a function of the point along the processing trajectory X. In the “online” quality assessment, the speed of the measurement of the processing result along the processing trajectory X with the sensors 2 preferably corresponds to the speed of the processing operation, that is to say the processing speed, for example the welding speed v.sub.s(x) in a welding process.

[0037] As an alternative or in addition to the “online” quality assessment, according to FIG. 2B, an “offline” quality assessment can also take place, in which the workpiece W or the processing result R(x) is measured along the processing trajectory X after the processing operation has taken place with corresponding sensors 2, for example optical sensors 3, cameras 4, or X-ray sensors 5 or the like, and corresponding sensor signals S.sub.j(x) are provided. In the case of the “offline” quality assessment, the speed of the measurement of the processing result R(x) along the processing trajectory X with the sensors 2 after completion of the processing of the workpiece W can be higher than the processing speed. Nevertheless, in contrast to the “online” quality assessment, the “offline” quality assessment represents additional time expenditure.

[0038] In FIG. 2C, a method of quality assessment of the processing operation is outlined, in which the workpiece W is destroyed along the processing trajectory X for the analysis of the processing result R(x), in that microsections of the workpiece W are produced in the region of the processing result R(x) at a plurality of points of the processing result R(x) along the processing trajectory X. These microsections can be measured with corresponding sensors 2 and image-processing methods and provide sensor signals S.sub.j(x), which likewise provide information about the quality of the processing operation on the workpiece W and of the processing result R(x) at specific points along the processing trajectory X. For example, during a welding process, such a microsection can provide indications of the weld penetration depth of the weld seam as the processing result R(x).

[0039] As illustrated in FIG. 2D, quality parameters Q.sub.k(x), which characterise the quality of the processing result R(x) of the processing operation for the respective processing task, are determined from the various sensor signals S.sub.j(x) of the processing result R(x). Depending on the processing task, different quality parameters Q.sub.k(x), which quantify the quality of the processing result R(x) along the processing trajectory X, can exist. In order to assess the quality, the at least one quality parameter Q.sub.k(x) is now compared with quality parameter threshold values, for example an upper quality parameter threshold value Q.sub.k,o(x) and a lower quality parameter threshold value Q.sub.k,u(x). If the quality parameter threshold values Q.sub.k,o(x), Q.sub.k,u(x) are exceeded, the quality is assumed not to be fulfilled, which is marked with “NIO” (not in order). If all quality parameters Q.sub.k(x) are within their quality parameter threshold values Q.sub.k,o(x), Q.sub.k,u(x), the quality of the processing operation is considered to be fulfilled and the workpiece W is classified as “IO” (in order). If there are deliberately manual or automatically performed changes in the processing parameters ΔP.sub.i(x) during the processing operation, the processing result R′(x) consequently changes. If this changed processing result R′(x) is now measured with the sensors 2 and quality parameters Q′.sub.k(x) are determined therefrom and compared with the original quality parameter threshold values Q.sub.k,o(x), Q.sub.k,u(x), then generally false quality statements result. Therefore, the object of the present invention is to automatically take into consideration the deliberately performed changes in the processing parameters ΔP.sub.i(x) during the processing operation in the assessment of the quality of the processing operation and of the changed processing result R′(x). This will preferably result in adapted and changed quality parameter threshold values Q′.sub.k,o(x), Q′.sub.k,u(x).

[0040] FIG. 3 shows a schematic representation of the method according to the invention for assessing the quality of a processing operation and of the processing result R(x) along the processing trajectory X on a workpiece W. The device 1 for quality assessment of the processing operation receives the various sensor signals S.sub.j(x) which measure the processing result R(x) along the processing trajectory X during the processing operation by sensors 2 mounted on the processing head 12 of the processing device 10 (“online” quality assessment). Alternatively or additionally, the sensor signals S.sub.j(x), which were recorded after the processing operation by measuring the processing results R(x) along the processing trajectories X with corresponding sensors 2, are provided to the device 1 for quality assessment. At least one quality parameter Q.sub.k(x) is determined from the at least one sensor signal S.sub.j(x) and the at least one quality parameter Q.sub.k(x) is compared with quality parameter threshold values Q.sub.k,o(x), Q.sub.k,u(x) for assessing the quality of the processing operation and the processing result R (x) along the processing trajectory X. If the quality parameter threshold values Q.sub.k,o(x), Q.sub.k,u(x) are exceeded, the quality is assumed not to be fulfilled and the workpiece is classified as “NIO” (not in order), which is indicated on a display 13, for example. If all quality parameters Q.sub.k(x) are within their quality parameter threshold values Q.sub.k,o(x), Q.sub.k,u(x), the quality of the processing operation and of the processing result R(x) is considered to be fulfilled and the workpiece W is classified as “IO” (in order), which is indicated on the display 13, for example. In addition, if a quality parameter threshold value Q.sub.k,o(x), Q.sub.k,u(x) is exceeded, a warning can also be output, for example an acoustic warning on a loudspeaker 14.

[0041] According to the invention, when assessing the quality of the processing operation and the processing result R(x) along the processing trajectory X, performed changes in the processing parameters ΔP.sub.i(x) are automatically taken into consideration from the target values of the processing parameters P.sub.i,soll(x) during the processing of the processing trajectory X of the workpiece W, which is illustrated by the connection of the processing device 10 to the device 1 for assessing the quality of the processing operation. This can take place, for example, in that, on the basis of the changed situation, also adapted quality parameter threshold values Q′.sub.k,o(x), Q′.sub.k,u(x) are defined, which are stored for the changes in the processing parameters ΔP.sub.i(x) or are defined by corresponding calculation rules. The automatic assessment of the quality of the processing operation and of the changed processing result R′(x) is thus automatically based on the adapted quality parameter threshold values Q′.sub.k,o(x), Q′.sub.k,u(x), as a result of which the reliability of the quality monitoring can be increased. Furthermore, this makes the quality assessment suitable for adaptive processing systems. As a result, even workpieces W which, on the basis of customarily occurring tolerances, can be machined with changed processing parameters in accordance with the changes in the processing parameters ΔP.sub.i(x) and can provide other processing results R′(x) as ideal workpieces W, can be found to be “IO” (in order) by the quality-assessment system, without the need for a complex manual check. The adapted quality parameter threshold values Q′.sub.k,o(x), Q′.sub.k,u(x) can be defined from stored quality parameter threshold values Q.sub.k,o,g(x), Q.sub.k,u,g(x), which are determined from test processing operations for specific processing parameters P.sub.i(x), for example by interpolation of the stored quality parameter threshold values Q.sub.k,o,g(x), Q.sub.k,u,g(x).

[0042] FIG. 4 shows an example of a deliberate change in the processing parameters ΔP.sub.i(x) during a processing operation and its consideration in the quality assessment of the processing operation using a welding process. In the left-hand part of the figure, a workpiece W is shown in sectional view at the top before the processing and below it after the processing or after the welding process. This involves the passage of an overlap weld seam on two overlappingly arranged workpieces W. The workpieces W usually rest on top of one another without a gap and the welding process is carried out with pre-set welding parameters. In quality monitoring, for example, the width B(x) and the height H(x) of the weld seam N are determined as quality parameters along the processing trajectory X and are compared with threshold values for the width B.sub.o(x), B.sub.u(x) and height H.sub.o(x), H.sub.u(x) of the weld seam N. If the conditions B.sub.u(x)<B<B.sub.o(x) and H.sub.u(x)<H<H.sub.o(x) are met, the quality of the processing operation is assessed positively and the workpiece is classified as “IO”.

[0043] In practice, tolerances usually occur, which can lead, for example, to a gap d between the workpieces W, as shown in the right-hand part in FIG. 4. During the welding process, these changed conditions are acted upon, for example, manually or automatically (in an adaptive welding process), in that, for example, the conveying speed v.sub.d(x) of the welding wire and the welding current I(x) are increased and the welding speed v.sub.s(x) is reduced. This results in a weld seam N having a greater width B′ and a greater height H′ than in the processing of the workpiece W without a gap d (left-hand part in FIG. 4). If the quality assessment is carried out without automatic consideration of the changed conditions and the deliberately performed changes in the processing parameters, the width B′ and height H′ of the weld seam N would be considered as inadmissible and the quality of the processing operation would be assessed negatively and the workpiece would, for example, be marked as rejected (“NIO”: not in order) or sent for manual checking or post-processing.

[0044] In the method according to the invention for quality assessment, the performed changes in the processing parameters ΔP.sub.i(x) are now taken into consideration in that the deliberately performed changes in the processing parameters ΔP.sub.i(x) (here, for example, the increases in the conveying speed v.sub.d(x) and the welding current I(x) and the reduction in the welding speed v.sub.s(x)) are made known to the quality assessment and are taken into consideration in the assessment of the quality. For example, threshold values of the quality parameters Q′.sub.k,o(x), Q′.sub.k,u(x) adapted on the basis of the changes in the processing parameters ΔP.sub.i (x) are defined for the assessment of the quality of the processing operation. In the example shown, the upper and lower threshold values for the width B′.sub.o(x), B′.sub.u(x) of the weld seam N and the upper and lower threshold values for the height H′.sub.o(x), H′.sub.u(x) of the weld seam N would be adapted to the changed welding parameters. As a result, the changed processing result R′(x) or the changed weld seam N′ in the right-hand part in FIG. 4 is also correctly assessed positively with regard to quality, since the conditions B′.sub.u(x)<B′<B′.sub.o(x) and H′.sub.u(x)<H′<H′.sub.o(x) are fulfilled. Due to the automatic consideration of the deliberately performed changes in the processing parameters ΔP.sub.i(x) in the quality monitoring, the workpiece W can thus also be correctly classified as “IO” in this case and a manual checking of the workpiece W can be omitted.

[0045] The adapted hold values of the quality parameters Q′.sub.k,o(x), Q′.sub.k,u(x) in the event of changes in the processing parameters ΔP.sub.i(x) can be filed and stored in Tables or according to specific rules like the original threshold values of the quality parameters Q.sub.k,o(x), Q.sub.k,u(x) for the normal processing parameters P.sub.i(x). Processing parameters P.sub.i(x) lying between the stored values and threshold values of the quality parameters Q.sub.k,o(x), Q.sub.k,u(x) can be determined by interpolation methods. The quality assessment system has access to this data, irrespective of where they are available or stored. Instead of an upper and lower threshold values of the quality parameters Q.sub.k,o(x), Q.sub.k,u(x), a quality parameter mean value Q.sub.k,m(x) and a maximum quality parameter fluctuation range ΔQ.sub.k around this mean value can also be used to assess the quality of the processing result R(x).