Method and computer system for characterizing a sheet metal part

Abstract

A method for the characterization of a sheet metal forming product uses the correlation of material flow data to a priori calculated or measured data. It determines whether the product falls within the acceptable production limits in terms of quality, areas of potential defects and an approximation of the process parameters prevailing during its production. The characterization is performed in real-time during production, tool deployment or try-out. The method includes the steps of: providing physical dimensions of an actual sheet metal part; a feature extractor computing, from these physical dimensions, a measured material flow metric representative of the geometry of the part after the forming operation; and a matching unit determining, from reference data and the measured material flow metric, a matching forming operation data set whose associated simulated material flow metric most closely matches the measured material flow metric.

Claims

1. A method for characterizing a sheet metal part, the method comprising the steps of: a sensing operation providing physical dimensions of an actual sheet metal part before, during and/or after a forming operation; a feature extractor computing, from these physical dimensions, a measured material flow metric, the measured material flow metric being representative of a geometry of the actual sheet metal part after the forming operation; retrieving, from a computer readable data storage device, reference data that represents the results of a set of simulations of the forming operation, each simulation being associated with a forming operation data set that characterizes the simulation, and a simulated material flow metric that is a result of the simulation; a matching unit determining, from the reference data and the measured material flow metric, a matching forming operation data set whose associated simulated material flow metric most closely matches the measured material flow metric and outputting, on a display device or on the actual sheet metal part, a visual representation of data of the matching forming operation data set or putting a human or machine readable marking on the actual sheet metal part representative of the forming operation data set.

2. The method of claim 1, wherein the reference data comprises at least one of a simulation data set and class definition data and mapping information; wherein the simulation data set comprises a plurality of forming operation data sets and associated simulated material flow metrics, the forming operation data sets comprising at least one of: process parameters of the forming operation, forming operation result data and a geometry of a simulated sheet metal part, and the simulated material flow metric being representative of the geometry of a flange area of the simulated sheet metal part after the forming operation; and the class definition data defines classes within the simulated material flow metrics; the mapping information defines one or more mapping functions, defining a mapping from material flow metrics to forming operation data sets, with either a set of one or more mapping functions being defined globally over all material flow metrics, or a set of one or more local mapping functions for each class, being defined over the material flow metrics corresponding to that class.

3. The method of claim 1, wherein the matching forming operation data set comprises at least one of: process parameters of the forming operation; the geometry of the simulated sheet metal part after the forming operation; state variables of the simulated sheet metal part after the forming operation; areas of defects of the part shaped by the forming process; and qualitative or quantitative information on how to change the process parameters of a forming operation in order to achieve a desired process performance.

4. The method of claim 1, wherein the matching unit performs the steps of: given the measured material flow metric, determining a class into which this measured material flow metric falls; returning, as matching forming operation data set, one of the forming operation data sets with this class.

5. The method of claim 1, wherein the matching unit performs the step of: returning, as matching forming operation data set, a matching forming operation data set inferred from the measured material flow metric by means of a mapping function.

6. The method of claim 1, wherein the measured material flow metric and the simulated material flow metrics are either flange or a draw-in distribution or a combination of both.

7. The method of claim 1, comprising providing a data storage device comprising stored non-transitory computer program code which, when executed performs the sensing, the computing, the retrieving, and the matching.

8. The method of claim 1, comprising providing a computer system for characterizing the sheet metal part, the computer system comprising a data processor, the computer system being configured and programmed to execute the sensing, the computing, the retrieving, and the matching.

9. The method of claim .[.8.]. .Iadd.1.Iaddend., comprising providing a sensing device arranged to provide physical dimensions of the actual sheet metal part after the forming operation.

10. A method for generating reference data for characterizing a sheet metal part, the method comprising the steps of: a) providing forming operation result data, the forming operation result data comprising at least a geometry of a simulated sheet metal part after the forming operation; b) a postprocessor computing, from a forming operation result data, a simulated material flow metric, the simulated material flow metric being representative of the geometry of the simulated sheet metal part after the forming operation; c) storing, in a non-transitory computer readable storage medium, the simulated material flow metric and a forming operation data set, the forming operation data set comprising at least one of the process parameters and the forming operation result data; d) repeating the preceding steps several times with different forming operation result data and storing, in a computer readable data storage device, in each case the forming operation data set and the associated simulated material flow metric, the entirety of forming operation data sets and associated simulated material flow metrics constituting a simulation data set; e) computing and storing, in the computer readable data storage device, mapping information that defines a relationship between material flow metrics and forming operation data sets and outputting, on a display device or on an actual sheet metal part, a visual representation of data of at least one of the forming operation data sets or putting a human or machine readable marking on the actual sheet metal part representative of at least one of the forming operation data sets.

11. The method of claim 10, wherein the step of providing forming operation result data comprises the steps of: f) providing a set of simulation parameters, the simulation parameters defining at least process parameters of the forming operation performed on the sheet metal part; g) a numerical simulator simulating execution of the forming operation on the sheet metal part, the forming operation being characterized by the simulation parameters, and the numerical simulator thereby computing the forming operation result data; wherein the repeating of step a) for providing forming operation result data is done using different sets of simulations parameters.

12. The method of claim 10, comprising the further steps of: h) a class extractor analysing the material flow metrics generated by the several simulations and identifying a plurality of classes within these simulated material flow metrics; and i) storing, in the computer readable data storage device, class definition data defining these classes, wherein the mapping information associates one or more simulation data set with each class, for further use as reference data for characterizing the sheet metal part.

13. The method of .[.one of.]. claim 10, wherein the mapping information defines one or more mapping functions, defining a mapping from material flow metrics to forming operation data sets, with either a set of one or more mapping functions being defined globally over all material flow metrics, or a set of one or more local mapping functions for each class of a plurality of classes within the material flow metrics, the local mapping function being defined over the material flow metrics corresponding to that class.

14. The method of claim 10, comprising providing a data storage device comprising stored non-transitory computer program code which, when executed on a computer system, performs the providing, the computing, the storing, and the repeating.

.Iadd.15. A method for characterizing a sheet metal part, the method comprising the steps of: a sensing operation providing physical dimensions of an actual sheet metal part before, during and/or after a forming operation; a feature extractor computing, from these physical dimensions, a measured material flow metric, the measured material flow metric being representative of the geometry of the actual sheet metal part after the forming operation; retrieving, from a computer readable data storage device, reference data that represents the results of a set of simulations of the forming operation, each simulation being associated with a forming operation data set that characterizes the simulation, and a simulated material flow metric that is a result of the simulation; a matching unit determining, from the reference data and the measured material flow metric, a matching forming operation data set whose associated simulated material flow metric most closely matches the measured material flow metric, wherein the matching forming operation data set comprises at least one of: process parameters of the forming operation; state variables of the simulated sheet metal part after the forming operation; based on at least one of process parameters and state variables of the matching forming operation data set, modifying process parameters; and performing a forming operation with the modified process parameters to produce a further sheet metal part. .Iaddend.

.Iadd.16. The method of claim 15, wherein the reference data comprises at least one of a simulation data set and class definition data and mapping information; wherein the simulation data set comprises a plurality of forming operation data sets and associated simulated material flow metrics, the forming operation data sets comprising at least one of: process parameters of the forming operation, forming operation result data and the geometry of a simulated sheet metal part, and the simulated material flow metric being representative of the geometry of the flange area of the simulated sheet metal part after the forming operation; and the class definition data defines classes within the simulated material flow metrics; the mapping information defines one or more mapping functions, defining a mapping from material flow metrics to forming operation data sets, with either a set of one or more mapping functions being defined globally over all material flow metrics, or a set of one or more local mapping functions for each class, being defined over the material flow metrics corresponding to that class. .Iaddend.

.Iadd.17. The method of claim 15, comprising the further step of outputting, on a display device or on the actual sheet metal part, a visual representation of data of the matching forming operation data set or putting a human or machine readable marking on the actual sheet metal part representative of the forming operation data set. .Iaddend.

.Iadd.18. The method of claim 15, wherein the matching forming operation data set comprises at least one of: the geometry of the simulated sheet metal part after the forming operation; areas of defects of the part shaped by the forming process; qualitative or quantitative information on how to change the process parameters of a forming operation in order to achieve a desired process performance. .Iaddend.

.Iadd.19. The method of claim 15, wherein the matching unit performs the steps of: given the measured material flow metric, determining a class into which this measured material flow metric falls; returning, as matching forming operation data set, one of the forming operation data sets with this class. .Iaddend.

.Iadd.20. The method of claim 15, wherein the matching unit performs the step of: returning, as matching forming operation data set, a matching forming operation data set inferred from the measured material flow metric by means of a mapping function. .Iaddend.

.Iadd.21. The method of claim 15, wherein the measured material flow metric and the simulated material flow metrics are either the flange or the draw-in distribution or a combination of both. .Iaddend.

.Iadd.22. The method of claim 15, comprising providing a data storage device comprising stored non-transitory computer program code which, when executed performs the sensing, the computing, the retrieving, and the matching. .Iaddend.

.Iadd.23. The method of claim 15, comprising providing a computer system for characterizing a sheet metal part, the computer system comprising a data processor, the computer system being configured and programmed to execute the sensing, the computing, the retrieving, and the matching. .Iaddend.

.Iadd.24. The method of claim 23, comprising providing a sensing device arranged to provide physical dimensions of an actual sheet metal part after a forming operation. .Iaddend.

.Iadd.25. The method of claim 15, comprising the step of using an evaluation of at least one of process parameters and state variables of the matching forming operation data set to do, during tryout or during production, at least one of: accept or reject the part; adjust the process and tools if the part is not acceptable. .Iaddend.

.Iadd.26. The method of claim 15, comprising the steps of during production, based on at least one of process parameters and state variables of the matching forming operation data set, determining potential defects on the part; and providing feedback to operators or equipment in order to return a process that drifts away from acceptable limits back under control. .Iaddend.

.Iadd.27. The method of claim 15, comprising the step of during production, providing for digital feedback for closed loop control of equipment at least one of additional quality control metrics, statistical information and advisory data. .Iaddend.

.Iadd.28. The method of claim 27, comprising the step of performing closed loop control of equipment based on the at least one of additional quality control metrics, statistical information and advisory data. .Iaddend.

.Iadd.29. The method of claim 28, comprising the step of performing a further forming operation to produce a further sheet metal part. .Iaddend.

.Iadd.30. The method of claim 15, comprising the steps of providing for an operator at least one of additional quality control metrics, statistical information and advisory data; displaying, on a display device, the at least one additional quality control metrics, statistical information and advisory data. .Iaddend.

.Iadd.31. The method of claim 15, comprising providing a data storage device comprising stored non-transitory computer program code which, when executed on a computer system, performs the providing, the computing, the retrieving, and the matching. .Iaddend.

.Iadd.32. A method for producing sheet metal parts, the method comprising the steps of: producing an actual sheet metal part by a forming operation; a sensing operation providing physical dimensions of the actual sheet metal part before, during and/or after the forming operation; a feature extractor computing, from these physical dimensions, a measured material flow metric, the measured material flow metric being representative of the geometry of the actual sheet metal part after the forming operation; retrieving, from a computer readable data storage device, reference data that represents the results of a set of simulations of the forming operation, each simulation being associated with a forming operation data set that characterizes the simulation, and a simulated material flow metric that is a result of the simulation; a matching unit determining, from the reference data and the measured material flow metric, a matching forming operation data set whose associated simulated material flow metric most closely matches the measured material flow metric, wherein the matching forming operation data set comprises at least one of: process parameters of the forming operation; and state variables of the simulated sheet metal part after the forming operation, based on at least one of process parameters and state variables of the matching forming operation data set, modifying process parameters; and performing a further forming operation with the modified process parameters to produce a further sheet metal part. .Iaddend.

.Iadd.33. An apparatus for characterizing a sheet metal part, comprising: a sensing device arranged to provide physical dimensions of an actual sheet metal part before, during and/or after a forming operation; a feature extractor arranged to compute, from these physical dimensions, a measured material flow metric, the measured material flow metric being representative of the geometry of the actual sheet metal part after the forming operation; a computer readable data storage device arranged to allow retrieving of reference data that represents the results of a set of simulations of the forming operation, each simulation being associated with a forming operation data set that characterizes the simulation, and a simulated material flow metric that is a result of the simulation; a matching unit arranged to determine, from the reference data and the measured material flow metric, a matching forming operation data set whose associated simulated material flow metric most closely matches the measured material flow metric, wherein the matching forming operation data set comprises at least one of: process parameters of the forming operation; state variables of the simulated sheet metal part after the forming operation; and a unit arranged to: based on at least one of process parameters and state variables of the matching forming operation data set, modify process parameters; and perform a forming operation with the modified process parameters to produce a further sheet metal part. .Iaddend.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) The subject matter of the invention will be explained in more detail in the following text with reference to preferred exemplary embodiments which are illustrated in the attached schematic drawings, in which:

(2) FIG. 1 is a top view of a simplified forming process where the left part of the drawing corresponds to the punch and sheet before forming and the right part of the drawing to the punch and sheet after drawing;

(3) FIG. 2 is a top view of a formed metal part where the draw-in and the flange can be seen;

(4) FIG. 3 shows possible alternatives of the flange distribution under varying process conditions;

(5) FIG. 4 presents a flowchart for extracting draw-in and flange distribution information from a set of simulations and calculating classes and inference models from these distributions;

(6) FIG. 5 presents a flowchart for extracting draw-in and flange distribution information from a digital model of an actual formed part and classifying it using the saved classes and inference models;

(7) FIG. 6 shows the structure of a system for determining reference data and inference models for characterizing a sheet metal part; and

(8) FIG. 7 shows the structure of a system for characterizing a sheet metal part.

(9) The reference symbols used in the drawings, and their meanings, are listed in summary form in the list of reference symbols. In principle, identical parts are provided with the same reference symbols in the figures.

DETAILED DESCRIPTION OF EMBODIMENTS

(10) In a preferred embodiment of the invention, a method is used to calculate material flow (for example draw-in and flange distributions) for a set of simulations, identify patterns within the distributions, calculate mappings between draw-in or flange distributions and process parameters and state variables. Further steps are to acquire a digital model of an actual formed part, extract required information to calculate the material flow distribution for the actual part and infer the actual distribution to the virtual distributions. These steps are preferentially implemented by a computer program which is executed on a data processing system. The computer program may have two parts, one for preparing data and one that works online. This separation is not mandatory, but improves the online efficiency. From the inference it is possible to extract the characterisation of the part in terms of state variables and process parameters. This characterisation is, in a further step, used to modify process parameters during tryout and production in order to achieve the desired part characteristics and determine potential defects on the part.

(11) FIG. 4 schematically illustrates the control flow of the preparatory phase of the method in a preferred embodiment of the invention. The method assumes that a material flow metric is selected and, in line with the requirements of this metric, there is a set of characteristic lines that can be used to calculate said metric. In the following the part outline and the punch opening line are considered to provide the draw-in or flange distribution, as one possible material flow metric, but other lines can be used as appropriate for the particular part. A prerequisite to the method is a multitude of simulation results, based on differing simulation parameters 21, where for each one there exists a set of initial parameters, a geometrical representation of the virtual formed part and state variables such as the thickness of the material of the formed part (forming operation result data 24). For each such simulation a pre-processor reads the virtual formed part geometry 41 and extracts the formed part outline 42 and the punch opening line 43. Given those two lines, the flange distribution is calculated 44. If the initial blank outline exists, the draw-in can also be calculated. The calculated lines and distributions are stored 45 as simulated material flow metrics 26 for later use.

(12) If classes are to be calculated 46, the calculated set of draw-in or flange distributions is analysed 47 using a classifying or pattern recognition method and the resulting class information is saved as class definition data 30 in the database 48. An example of classes within the draw-in is presented in FIG. 3.

(13) In order to extract useful patterns from the pool of stored material flow metrics (draw-in or whole sheet or other), one may assume without loss of generality that the distributions lie in the same multidimensional space. Techniques for pattern extraction and classification are known in the field of pattern recognition and can range from Bayesian networks to neural networks to linear or quadratic classifiers etc. A combination of techniques may be used to achieve the desired result. Some of the relevant techniques are: Principal component analysis, which can be used to identify the dominant modes in a set of patterns, their energies and which mode contributes to which pattern. Such a technique can be used to filter out perturbations and yield a handful of dominant patterns from hundreds of simulated material flow metrics. Linear discriminant analysis and the related Fischer's linear discriminant, which can be used to identify more directly the linear combination of features which separate two or more classes, but then the classes must be known in advance.

(14) Cluster analysis.

(15) In principle, if the number of classes is known, any pattern recognition technique can give a result. Principal components analysis is a good way to start with in order to determine the number and shape of classes. A classification algorithm can take advantage of other traits of the problem in order to identify interesting classes, such as the fact that usually larger deformations occur along the sides of the blank. Obviously, as the blank has a finite number of sides, combinations of side deformations may constitute a finite number of interesting classes of material flow metrics.

(16) Either for each one of the classes or for the whole population of material flow metrics 49, mapping functions or matching functions that define a relationship for mapping between material flow metrics and forming operation data sets 27 comprising e.g. process parameters and state variables are calculated 50 using statistical or other methods. The functions are saved 51 as mapping or matching information 31 in the database which concludes the preparatory phase of the computer program. Such mapping information may also be considered to be a surrogate model relating material flow metrics and forming operation data sets.

(17) FIG. 5 schematically illustrates the control flow of the real-time or online phase of the method in a preferred embodiment of the invention. By means of a sensing device 11, using manual measurements, an optical, scanning or other method, a digital two-dimensional or three-dimensional geometrical digital model 12 of the actual formed part 10 is acquired 52 that, depending on the calculation requirements for the material flow metric, may include one or more configurations of the actual formed part 10 before (i.e. the blank 3), during and/or after the forming operation. From this digital model 12 of the formed part, measured material flow metrics 14 such as e.g. the formed part outline 53 and the punch opening line 54 are extracted by a feature extractor 13. If there is information on the initial position of the sheet metal blank before the process, the initial blank outline 55 is extracted as well. The extracted lines are used to calculate the actual flange and draw-in distributions 56. If there are saved distribution patterns 57, as part of reference data 33, these are retrieved from the database and the actual distribution in question is matched to a pattern 58 by a matching unit 15. The distribution is then matched to an individual simulation 59, either within the pattern or within the whole population. If inference or mapping functions have been calculated 60, these are used to infer or to interpolate the distribution in question 61 to the functions.

(18) Inference models for mapping material flows to forming operation data can be developed using different techniques and depending on what the outcome might be. A neural network, for example, a simple feed forward with back propagation network, or a radial basis function (RBF) network can provide a mapping of a multidimensional input (in this case, the material flow metric) to a multidimensional output (in this case, forming operation data). Response surface and Kriging techniques can also be used. Bayesian networks can equally well be used to calculate the probability that some zones of the formed part may show particular quality problems.

(19) Either through matching or inference, the distribution is used to characterize the part 62, determining a matching forming operation data set 16 that characterizes the part. The characterization consists of process parameters and state variables for the actual part and mapping them from the original geometries to the actual geometry. The characterisation can also include additional quality control metrics, statistical information or any form of advisory data for the operator or digital feedback for the closed control loop of the equipment. Comparing the calculated state variables to the desired ones, areas of potential defects can be identified on the actual part 10. The characterization result is then displayed to the user 63 on a display device 17, for example by overlaying a colour coded representation of chosen state variables, parameters and/or fault probabilities on a 2D- or 3D model of the part. It is also possible to overlay the colour coded representation to a video image of the real part displayed either on a display device or in a wearable display system, thus allowing the user to identify and mark areas of potential quality problems for further inspection. In another embodiment, the affected area on the part is marked with spray or a marker, e.g. by a robotic device, or a barcode, RFID or other machine or human readable representation of data is attached to the part to make it possible to identify it in later inspection. Finally, the characterization result is saved in the database 64.

(20) FIG. 6 shows the structure of a system for determining reference data 33 for characterizing a sheet metal part, and also the data flow of a corresponding method. The system starts out with a set of simulation parameters 21, the simulation parameters 21 defining at least a tool geometry and process parameters 22 of a forming operation performed on the sheet metal part. A numerical simulator 23 is configured to simulate execution of the forming operation on the sheet metal part, the forming operation being characterised by the simulation parameters 21. By the simulation, the numerical simulator 23 computes forming operation result data (FORD) 24 comprising at least the geometry (that is, the 3D- or a 2D shape) of the simulated sheet metal part 3 after the forming operation. From this geometry, a postprocessor 25 computes a simulated material flow metric (sim MFM) 26. The simulated material flow metric 26 is representative of or related to the geometry of the flange area 8 of the simulated sheet metal part 3 after the forming operation, the flange area being the area between the edge of the metal sheet after forming and a predefined characteristic line such as the punch opening line. The simulated material flow metric 26 is, for example, a data set representing the draw-in or the flange distribution for the simulated part.

(21) The simulated material flow metric 26 is associated with a forming operation data set 27 (FODS) used in the generation of the material flow metric 26, and both are stored, in a computer readable storage medium. The forming operation data set 27 comprises at least one of the process parameters 22 and the forming operation result data 24. Through this association, it shall later be possible to determine forming operation data, given a measured material flow metric.

(22) The preceding steps are repeated several times with different simulation parameters 21. For each simulation, the forming operation data set 27 and the associated simulated material flow metric 26 is stored in a computer readable data storage device 32. The entirety (that is, over all simulations) of forming operation data sets 27 and associated simulated material flow metrics 26 shall be labelled a simulation data set 28 (sim DS). In other words, the simulation data set 28 comprises a plurality of forming operation data sets 27 and associated simulated material flow metrics 26.

(23) In principle, the information contained in this simulation data set 28 is sufficient to determine forming operation data, given a measured material flow metric. In order to facilitate and speed up the later online matching of measured material flow metrics and the retrieval of corresponding forming operation data, in a preferred embodiment of the invention, a class extractor 29 is configured to analyse the material flow metrics generated by the several simulations and to identify a plurality of classes within these simulated material flow metrics 26. Resulting reference data 33 for characterizing the sheet metal part comprises class definition data 30 (classdef) defining these classes, and mapping information 31 (mapinfo). In order to evaluate more precise FODS for the meas MFM, it is possible to use a surrogate model. This surrogate model, represented by the mapping information 31 defines the parameters of one or more mapping functions that constitute a mapping from material flow metrics to forming operation data sets, with either a single set of mapping functions being defined globally over all material flow metrics, or one set of local mapping functions for each class, being defined over the material flow metrics of that class. The reference data 33 is stored in a computer readable data storage device 32 for further use in the online characterisation of the sheet metal part.

(24) FIG. 7 shows the structure of a system for characterizing a sheet metal part, and also the data flow of a corresponding method. A sensing device 11 is arranged to measure physical dimensions 12 of the flange area of an actual sheet metal part 10 after a forming operation. The sensing device 11 is, for example, a camera or a 3D scanner or other contact-based or contactless measurement system, or a sensor incorporated in the deep drawing tool, as described e.g. in the initially mentioned publication by E. Doege et al, but can be as simple as a device used for taking manual measurements. Manual measurements may involve, for example, touch probes, chalk marks on sheet, a string to measure the length of lines or distances from draw beads, etc. The following steps are executed on a data processor 18, which may comprise, for example, dedicated hardware and/or a general-purpose computer or cluster of computers programmed to perform the method steps of feature extraction and matching, as described in the following: A feature extractor 13 computes a measured material flow metric 14, the measured material flow metric 14 (meas MFM) being representative of the geometry of a flange area 8 of the actual sheet metal part 10 after the forming operation. Reference data 33 is retrieved from a computer readable data storage device 32, the reference data 33 comprising at least one of a simulation data set 28 and class definition data 30 and mapping information 31. A matching unit 15 determines, from the reference data 33 and the measured material flow metric 14, a matching forming operation data set 16 (match FODS) whose associated simulated material flow metric 26 most closely matches the measured material flow metric 14. Most closely in this context is defined, for example, in terms of proximity to or inference from the simulated material flow metrics 26. A display device 17 is configured to display a visual representation of selected information, characterizing the actual sheet metal part 10, from the matching forming operation data set 16. This information is one of, for example, one or more process parameters, state variables and areas of defects of the part after forming.

(25) In one exemplary embodiment of the invention, the matching performed by the matching unit 15 can be limited to simply identifying the simulation data set 28 for which the corresponding simulated material flow metric 26 is closest to the measured material flow metric 14. The proximity can be expressed using different metrics, but to illustrate this process, a simple criterion is the minimum angle between the vectors of the simulated material flow metric 26 and the measured material flow metric 14. Both quantities can be represented as vectors of real numbers and have the same dimensionality since the sampling points are the same; therefore the angle between these vectors is trivial to calculate.

(26) A more elaborate evaluation of the matching forming operation data set 16 can involve the calculated mapping information 31. In this case, the set of one or more mapping functions is used to calculate the matching forming operation data set 16 from the measured material flow metric 14. The result can offer a more precise matching forming operation data set 16 than the simple matching, since, in the latter case, two slightly different measured material flow metrics 14 might be matched to the same matching forming operation data set 16. However, the result is dependent on the assumptions implicit in the surrogate model used for the calculation of the mapping information 31.

(27) In addition to the previous techniques for evaluating the matching forming operation data set 16, and in order to accelerate this process during the online use of the computer system, calculated class definition data 30 classes can be used. The evaluation can be done, in the same way as described so far, butinstead of using all the simulated material flow metric 26by first matching the measured material flow metric 14 to a class in class definition data 30 and then to one of the simulated material flow metrics 26 in that class. If for that class a mapping information 31 exists, this can be used to determine a more precise evaluation of a matching forming operation data set 16. The use of the classes accelerates the process in way of locating the measured material flow metric 14 to a subspace of the whole design space, so smaller surrogate models can be used but also in way of acting as a filter, where measured material flow metrics 14 that correspond to defect-free subspaces of the design space do not need further processing, at least not during the on-line phase.

(28) The invention is obviously not limited to the preferred embodiments described above by way of an example, but lends itself to modifications within the scope of the invention as defined in the claims below.

LIST OF DESIGNATIONS

(29) 1 blank 2 forming tool 3 formed part 4 draw-in 5 sheet metal blank outline 6 formed part outline 7 punch opening line 8 flange material, flange area 10 actual sheet metal part 11 sensing device 12 physical dimensions 13 feature extractor 14 measured material flow metric 15 matching unit 16 matching forming operation data set 17 display device 18 data processor 21 simulation parameters 22 process parameters 23 numerical simulator 24 forming operation result data 25 postprocessor 26 simulated material flow metric 27 forming operation data set 28 simulation data set 29 class extractor 30 class definition data 31 mapping information 32 data storage device 33 reference data