Method for Operating a Press, Computer Program and Electronically Readable Data Carrier

Abstract

A method for operating a press, wherein a relationship between a detected component property (current value) of the final product (e.g. surface quality), the provided material property of the semi-finished product (e.g. sheet thickness), and the detected production parameter (e.g. pressing pressure) is determined, for example, by a self-learning algorithm, on the basis of precedingly determined differential values between target and current values of the component property. The algorithm is subsequently used for targeted selection of samples for quality monitoring.

Claims

1-10. (canceled)

11. A method for operating a press, in which semifinished products are shaped into components, the method comprising: providing at least one material property of at least one semifinished product; detecting at least one production parameter that characterizes a status of the press during shaping of the at least one semifinished product to form at least one respective shaped component; selecting the at least one shaped component from a set of shaped components on a basis of the at least one material property of the at least one semifinished product underlying the at least one selected shaped component and/or on a basis of the at least one production parameter detected during the shaping of the at least one selected shaped component by way of an electronic computing device; detecting at least one component property of the at least one selected shaped component by way of a measuring device; determining at least one difference value describing a deviation of the detected component property of the at least one selected shaped component from a target value predetermined for a component type of the at least one selected shaped component; and providing the at least one difference value.

12. The method according to claim 11, comprising: carrying out the selection of the at least one shaped component on a basis of the at least one material property in response to the at least one material property having a specified distance from an expected value of the at least one material property.

13. The method according to claim 11, comprising: carrying out the selection of the at least one selected component by a self-learning algorithm and/or by at least one statistical method.

14. The method according to claim 11, comprising: refraining from selecting a formed component that is shaped during a starting process of the press as the at least one selected shaped component.

15. The method according to claim 11, comprising: selecting the at least one shaped component during a stationary status of the press at least with respect to the at least one production parameter.

16. The method according claim 11, comprising: selecting at least a first shaped component and a second shaped component as the at least one selected shaped component, wherein at least one material property of the first selected shaped component differs from at least one material property of the second selected shaped component.

17. The method according to claim 11, comprising: selecting at least two shaped components as the at least one selected shaped component, wherein at least one of the at least two selected components is selected by a random method.

18. The method according to claim 11, comprising: setting the at least one production parameter for subsequent shaping of a further shaped component in dependence on the at least one difference value.

19. A non-transitory electronically readable storage medium having items of electronically readable control information stored thereon that, when executed by an electronic computing device, cause the electronic computing device to perform a method comprising: providing at least one material property of at least one semifinished product; detecting at least one production parameter that characterizes a status of the press during shaping of the at least one semifinished product to form at least one respective shaped component; selecting the at least one shaped component from a set of shaped components on a basis of the at least one material property of the at least one semifinished product underlying the at least one selected shaped component and/or on a basis of the at least one production parameter detected during the shaping of the at least one selected shaped component by way of an electronic computing device; detecting at least one component property of the at least one selected shaped component by way of a measuring device; determining at least one difference value describing a deviation of the detected component property of the at least one selected shaped component from a target value predetermined for a component type of the at least one selected shaped component; and providing the at least one difference value.

20. The non-transitory electronically readable storage medium according to claim 19, wherein the method comprises: carrying out the selection of the at least one shaped component on a basis of the at least one material property in response to the at least one material property having a specified distance from an expected value of the at least one material property.

21. The non-transitory electronically readable storage medium according to claim 19, wherein the method comprises: carrying out the selection of the at least one selected component by a self-learning algorithm and/or by at least one statistical method.

22. The non-transitory electronically readable storage medium according to claim 19, wherein the method comprises: refraining from selecting a formed component that is shaped during a starting process of the press as the at least one selected shaped component.

23. The non-transitory electronically readable storage medium according to claim 19, wherein the method comprises: selecting the at least one shaped component during a stationary status of the press at least with respect to the at least one production parameter.

24. The non-transitory electronically readable storage medium according to claim 19, wherein the method comprises: selecting at least a first shaped component and a second shaped component as the at least one selected shaped component, wherein at least one material property of the first selected shaped component differs from at least one material property of the second selected shaped component.

25. The non-transitory electronically readable storage medium according to claim 19, wherein the method comprises: selecting at least two shaped components as the at least one selected shaped component, wherein at least one of the at least two selected components is selected by a random method.

26. The non-transitory electronically readable storage medium according to claim 19, wherein the method comprises: setting the at least one production parameter for subsequent shaping of a further shaped component in dependence on the at least one difference value.

Description

BRIEF DESCRIPTION OF THE DRAWING

[0034] FIG. 1 shows a schematic flow chart for a method for operating a press in which semifinished products are shaped into components.

DETAILED DESCRIPTION OF THE DRAWING

[0035] FIG. 1 shows a schematic flow chart of a method for operating a press, in which semifinished products, for example sheet metal plates, are shaped, in particular formed, into components, for example body components for motor vehicle construction. The press by which the method is operated can therefore in particular be a forming press but also, for example, a stamping press or the like.

[0036] It is a fact that not every component shaped using the press can be complexly measured in order to determine its accurate component properties or component quality. This would exceed the framework for time and/or costs, therefore in general only samples of the formed components are accurately measured. However, presently a selection of samples for the quality control is made randomly. Informative combinations of material properties of the semifinished product underlying the shaped component and production parameters or process parameters and the component quality resulting therefrom are thus not detected.

[0037] The method presented here is therefore based on the intention of compensating for the absence of desired data in order to, for example, improve a process control and thus an operation of the press.

[0038] Informative combinations of material properties of the semifinished product underlying the shaped component and production parameters or process parameters and the component quality resulting therefrom can be detected by the method. For this purpose, the presented method has several steps:

[0039] In a first step S1 of the method, at least one material property of the respective semifinished product is provided. The material property here is, for example, a thickness of the semifinished product, tensile strength, and/or further properties that characterize the semifinished product and are relevant for the shaping.

[0040] In a second step S2 of the method, at least one production parameter is detected, such as a setting of displacement cylinders which permit influencing of the contact pressure between a die, a blank, and the blank holder in the toolin the forming tool. Furthermore, a drawing aid setting and/or a stroke number can be detected as the production parameter. In addition, for example, a process duration of the press could be detected. The production parameter characterizes a status of the press during the shaping of the respective semifinished product to form the respective component.

[0041] In a third step S3 of the method, at least one of the shaped components is selected from a set of the shaped components on the basis of the at least one material property of the in particular individual semifinished product underlying the selected component and/or on the basis of the at least one production parameter detected during the shaping of the at least one selected component or the production parameter used during shaping by an electronic computing device. The set corresponds in particular to the entirety of the set formed into the components from the provided semifinished products while the press is operated by the method.

[0042] In a fourth step S4 of the method, at least one component property is detected, in particular the component quality or the component grade, of the selected component by a measuring device. The measuring device is, for example, a separately provided measuring stand, in particular having sensors, in which the selected component, which represents a sample, can be measured more precisely or accurately than is possible, for example, by so-called in-line sensors during the shaping.

[0043] Subsequently, in a fifth step S5 of the method, a difference value is determined, which describes a deviation of the detected component property of the at least one selected component, thus the sample, from a target value predetermined for a component type of the component, thus the model of the component, for example a specific body component. In other words, it can be determined in particular in step S5 whether the component quality of the component selected as a sample meets the requirements for the general component quality.

[0044] Finally, in the sixth step S6 of the method, the difference value is provided, so that it can be used, for example, for a later change of the at least one production parameter.

[0045] Therefore, in particular in a further step of the method, for example, the at least one production parameter can be produced for subsequent shaping of a further component in dependence on the provided difference value.

[0046] In step S3, the selection is made in particular on the basis of the electronic computing device by machine learning, and therefore, for example, by a self-learning algorithm and/or by a neural network. Additionally or alternatively, statistical methods can furthermore be used for this purpose.

[0047] In particular, it is advantageous for a particularly advantageous operation of the press if a selection of the at least one component takes place on the basis of the at least one material property when these material properties deviate from a specified norm or a target property of the semifinished product. Thus, for example, a sheet thickness of a semifinished product can be greater than a specified sheet thickness. The component shaped from this semifinished product would therefore be a candidate for the selection by the electronic computing device. Influences of the semifinished product properties on the component quality can advantageously be determined by the selection of components, the underlying semifinished products of which deviate from the norm. Thus, for example, boundary conditions for the shaping by the press can furthermore be determined.

[0048] In addition, it is advantageous for the selection of the sample in step S3 if no component is selected during a starting process of the press. Additionally or furthermore, it is advantageous if the selection takes place with a stationary status of the press or with a stationary status of at least the at least one production parameter.

[0049] If several samples, thus at least two components, are selected instead of the at least one sample, it is advantageous if the material properties of the semifinished product underlying the respective selected component differ, so that the material property of the semifinished product of the first sample is different from the material property of the semifinished product of the second sample.

[0050] Additionally or alternatively, it can furthermore be advantageous upon the selection of several samples if at least one of the samples is randomly selected in addition to the samples selected by the algorithm of the electronic computing device.

[0051] Targeted, automated taking of samples for quality assurance based on the algorithm of the electronic computing device is thus implemented by the presented method. The quality or the material property of the semifinished products and the status of the production process in the form of the at least one production parameter are taken into consideration here. Both aspects, thus the at least one material property and the at least one production parameter, can take influence on the component quality in combination. This can be particularly advantageously determined and/or established by the method. It can thus be reasonable, for example, if semifinished products which are formed, for example, as particularly thick plates are checked with respect to their dimensional accuracy after the forming into the resulting components. A quality control based, for example, on the plate thickness is thus enabled by the selection of these components, by which a relationship can be determined between the plate thickness and the component property. The different thicknesses of the semifinished products are generally not based here on semifinished products having a greater thickness deliberately being used. These are undesired variations which can be within a specification interval.

[0052] It is to be noted here that such an analysis is first enabled when multiple such studies have been carried out, i.e., when the method is repeated multiple times or multiple components are selected from the set of deformed components. Advantageously, instead of the at least one material property, multiple material properties, for example a lubricant quantity and/or a roughness of the semifinished product, are observed in addition to the sheet thickness. In addition, the at least one production parameter and therefore the process conditions are additionally observed during the method. It can thus be ensured that a selection for the samples and thus a taking of samples only takes place, for example, if tools of the press or the press have reached a stationary statusin particular a temperature status. Furthermore, the taking or selection of the sample is not to take place immediately after a production interruption, since kinematics of the press can have changed during a restart in the first produced components, for example.

[0053] The advantageous algorithm for the method carried out by the electronic computing device can therefore find the optimum point in time for a selection of the at least one component and thus the samples during the production or the shaping of the components themselves and at the same time take into consideration that both semifinished products having standard values of the material properties and also having material properties deviating from the standard are fed to the quality check or the detection of the component property. In order to nonetheless also be able to determine unexpected effects, furthermore a random selection of the samples can additionally take place.

[0054] Targeted determination and collection of the difference values is thus enabled by the method, by which a process control can take place even without the use of a costly and time-intensive continuous detection of the quality of all produced components. In addition, quality criteria can also be taken into consideration which cannot advantageously be detected using currently available sensorsat least during the production.

[0055] The method or the steps for carrying out the method can be provided or made available as a computer program for the electronic computing device, in particular on an electronically readable data carrier.

[0056] An optimization of the sample taking for the quality assurance for implementing particularly advantageous operation of the press can be achieved by the method presented here.

LIST OF REFERENCE SIGNS

[0057] S1 first step [0058] S2 second step [0059] S3 third step [0060] S4 fourth step [0061] S5 fifth step [0062] S6 sixth step