Manufacturing system and method for nesting subspaces for manipulating a cutting process

Abstract

When nesting subspaces (9A‑9F), an evaluation algorithm (44) is used to generate evaluation data, settlement data and / or sequence data (43”) with the aid of at least one data aggregation routine. In this case, the settlement data has an effect on the generation of new sequence data (43”) in order to improve the arrangement of the nested subspaces (9A‑9F) with respect to the evaluation criteria.

Description

Technical Field

[0001] The invention relates to the nesting of workpieces cut by means of a flatbed machine tool on an output plate, and in particular to a method for nesting a subspace for controlling a cutting process of a flatbed machine tool (e.g. a flatbed laser cutting machine), the subspace corresponding to the workpiece. The invention also relates to a manufacturing system having a flatbed machine tool. Background Art

[0002] Nesting is the positioning of the workpieces on the raw sheet as the output sheet for the laser cutting process. In the sheet metal processing industry, the nesting of the workpieces to be cut on the raw sheet is part of the production process, wherein the nesting results in a specific layout of the cutting lines. The result of the nesting process (nesting) in the phase and cutting phase is also referred to as the nesting plan, according to which the workpieces are cut from the raw sheet along the cutting lines defined therein.

[0003] When planning a laser cutting process, a geometric nesting can first be performed. For this purpose, quality parameters such as the residual material web width, i.e. the material width that should remain as residual material at least between two workpieces, can be specified. Based on the calculated geometric nesting, a sequence of movements, in particular the best possible sequence of movements, can then be determined for the processing head providing the laser beam with respect to the workpieces to be cut out. However, it has been recognized that all known nesting results can always be further improved and that existing methods do not always allow for optimal nesting. Summary of the invention

[0004] One aspect of the disclosure is based on the task of specifying an improved nesting process for workpieces to be cut. Another aspect of the disclosure is based on the task of improving the process efficiency, in particular the material efficiency and / or the time efficiency, for the cutting process based on a corresponding nesting arrangement of the subspaces and a travel path based on which the nesting is based, the travel path comprising the contours of the subspaces and the connecting paths between the contours of the subspaces.

[0005] At least one of these objects is achieved by a method for nesting subspaces for controlling a cutting process with a flatbed machine tool according to claim 1 and by a production system according to claim 10. Developments are specified in the dependent claims.

[0006] One aspect of the present disclosure relates to a method for nesting subspaces, wherein the subspaces are arranged in a two-dimensional plan space and bounded by contour lines in the two-dimensional plan space, wherein the subspaces are configured to manipulate a cutting process of a flatbed machine tool to cut a workpiece from a material sheet along at least one cutting line, the cutting line corresponding to the contour line of the subspace. The method comprises the following steps:

[0007] a. Read in the evaluation criteria for the arrangement of nested subspaces;

[0008] b. generating sequence data for arrangement of nested subspaces;

[0009] c. generating evaluation data by evaluating the sequence data with the aid of an evaluation algorithm;

[0010] d. Generate result data based on the combination logic of evaluation data and evaluation criteria;

[0011] e. generating settlement data from the sequence data, evaluation data and result data with the aid of an evaluation algorithm;

[0012] f. generating other series data by means of evaluation algorithms taking into account the settlement data; and

[0013] g. Repeat steps c to f until the result data exceeds the preset range.

[0014] In this case, when generating evaluation data, settlement data and / or other sequence data, the evaluation algorithm implements at least one data aggregation routine. The data aggregation routine aggregates a plurality of input data into output data when it is activated. The input data has at least two of the following data types:

[0015] The sequence data read in by the evaluation algorithm,

[0016] The evaluation data generated by the evaluation algorithm,

[0017] By evaluating the settlement data generated by the algorithm,

[0018] the output data of another data aggregation routine, and

[0019] Output data from a previous run of the same data aggregation routine.

[0020] The output data affects at least one of the following data types:

[0021] By evaluating the sequence data generated by the algorithm,

[0022] The evaluation data generated by the evaluation algorithm, and

[0023] Settlement data generated by the evaluation algorithm.

[0024] In another aspect, a manufacturing system has a flatbed machine tool for cutting workpieces from a material sheet according to a workpiece-specific cutting profile, an off-site data processing system and / or a local manufacturing control system. The off-site data processing system and / or the local manufacturing control system are configured to implement the previously outlined method in order to determine an arrangement of subspaces. The off-site data processing system and / or the local manufacturing control system are further configured to output the arrangement of the subspaces as control signals to the flatbed machine tool in order to cut workpieces corresponding to the subspaces from the material sheet.

[0025] In some embodiments, the evaluation criteria can be at least partially predetermined by a user. Alternatively or additionally, these evaluation criteria can be at least partially predetermined by a control device, in particular a superior control device. The evaluation criteria can include variables corresponding to the arrangement of the subspaces. These variables can characterize the overlap of the subspaces, the relative angles of the segments of the contour lines (which may trigger a beam break during the cutting process) and / or the duration corresponding to the cutting process, in particular taking into account thermal effects. The evaluation data can represent an evaluation of the variables corresponding to the evaluation criteria.

[0026] With the methods and systems disclosed herein, improvement parameters such as material efficiency, task elapsed time and quality can be improved more flexibly than before. These methods and systems are particularly flexible in matching different nesting schemes.

[0027] In some embodiments, the result data include the following data: the data define the material efficiency of the arrangement of the improvement parameters, in particular the subspaces, and define the quality of the workpiece produced. The combination logic may include the following steps: in these steps, a comparison of the evaluation data with the evaluation criteria, a difference determination, a ratio formation determination and / or a correlation determination is performed.

[0028] In some embodiments, the evaluation algorithm may include one or more data aggregation routines. The evaluation algorithm may be designed to activate one or more data aggregation routines multiple times, in particular more than ten times, in particular more than one hundred times, in particular more than one thousand times, in particular more than ten thousand times, and the evaluation algorithm assigns output data of another data aggregation routine or the same data aggregation routine previously run as input data to the data aggregation routine at least once. The evaluation algorithm may also be designed to always activate one or more data aggregation routines with one of the settlement data and other data types as input data. In addition, the data aggregation routine may be designed to link, in particular multiply, the settlement data with one of the other input data.

[0029] In some embodiments, the settlement data are associated with determined input data of the data aggregation routine. These settlement data can be linked, in particular multiplied, with these input data. The settlement data may include the following data: these data are constructed to improve the arrangement of the nested subspaces, in particular to improve the corresponding evaluation data and / or result data. The settlement data may include the following data in particular: these data allow the determination of which input data have an effect that is particularly as positive as possible on the result data and / or evaluation data. The settlement data corresponding to these input data can then be adjusted in particular in such a way that the linking, in particular multiplication, of the settlement data corresponding to the input data leads to the output data affecting the result in a particularly positive manner as possible, thereby continuously improving the result. Optionally, the effect of the settlement data on other evaluation data and / or result data can be determined.

[0030] Particularly advantageously, the method and / or the device can be used in industrial production with computer-based production control for processing flat, especially bending-resistant objects, especially sheet metal parts. For such objects, such a nesting method is particularly advantageous because the evaluation can depend on a very large number of criteria. These criteria may partially influence each other and can therefore only be calculated in an expensive manner in an automated determination. Examples of such bending-resistant objects are plates made of metal, glass, plastic, coated materials (e.g. coated plates made of plastic, wood, metal, glass, etc.).

[0031] The method and / or the device can be used particularly advantageously in industrial production using a laser processing machine, in particular a laser cutting machine.

[0032] It is particularly advantageous if the production control is also based at least partially on an off-site data processing system. Parameters, in particular weighting variables, used to change, in particular to improve, the algorithm of a first production plant can then also be used in other production plants and vice versa. Thus, a much larger database is available and the nesting results for each individual production run can be significantly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The disclosure here allows at least some improvements from the concepts of the prior art. In particular, further features and their suitability for the purpose can be seen from the following description of the embodiments based on the drawings. The drawings show:

[0034] Figure 1 A schematic spatial representation of a flatbed machine tool is shown,

[0035] Figure 2 A schematic diagram showing a nested schedule, and

[0036] Figure 3 A flow chart of a method for generating a nesting of subspaces for controlling a cutting process of a flatbed machine tool is shown. DETAILED DESCRIPTION

[0037] In particular in flatbed laser cutting machines, the two-dimensional (2D) nesting problem described here can be solved in terms of reducing the raw materials to be used, since the raw materials usually constitute a large part of the total cost. However, other aspects can also be considered. For example, in a flatbed laser machine, the relative position of the workpieces produced in the process relative to the supporting web of the laser cutting machine can be considered. This is disclosed, for example, in the applicant's German patent application 10 2018 124 146 entitled "Nesting of workpieces for cutting processes in flatbed machines" and filed on September 26, 2018, and in the German patent application entitled "Evaluation of workpiece positions in nested arrangements" (filed on the same day as the present application). The patent applications mentioned are all incorporated herein.

[0038] In addition, as disclosed in EP 2 029 313 B1, a collision check can be performed between the course of the cutting line and the support point tip. In addition, as disclosed in EP 2 029 316 B1, a workpiece support can be realized by means of a positionable support point tip.

[0039] A nesting scheme may be used as disclosed in JA Bennell et al., “The geometry of nesting problems: A tutorial”, European Journal of Operational Research 184 (2008) pp. 397-415.

[0040] In the calculated geometric nesting, a travel sequence, in particular the best possible travel sequence, can be determined with respect to the workpiece to be cut, wherein improvements can be made, for example, with the aid of a traveling salesman approach, for example.

[0041] The aspects described here are based in part on the knowledge that when nesting subspaces in the planning space (corresponding to the arrangement of the workpieces on the plate from which the workpieces are cut), the efficiency of the underlying cutting process can be incorporated into the evaluation method, more precisely in particular into the new nesting of the subspaces or the generation of the underlying sequence. In this case, the method can continue until a criterion such as material efficiency is achieved.

[0042] Thus, with the aid of the method proposed here, it is possible to achieve roundtripping between nestings of subspaces and an improvement of the cutting process, for example an improvement of the travel path, in the evaluation. Here, the travel path refers to the path that the laser head travels relative to the material plate between the cutting processes. This can be performed, for example, as follows: In a first step, a nesting result is generated, wherein instructions for the workpiece arrangement (for example, bottom-left placement) have already been applied in order to create an initial nesting result of sufficient quality. In the first step, configuration parameters such as the residual material web width, i.e. the width of the material that should at least remain as residual material between the two workpieces, can also be specified; however, this is optional. In a second step, the quality of the nesting result is evaluated. In this case, reference points of the subspaces (for example, penetration points or pressure points) can, for example, represent output data that can be used in the evaluation of the travel path. The reference points can, for example, be represented as parts of a polygonal column or a polygonal column to indicate the cutting process. For example, the overlap of the subspaces / workpieces, the angle at which a beam interruption is expected to occur during the cutting process, or the duration required for the laser cutting taking into account thermal effects can also be taken into account. The evaluation result is used to generate a new nesting. Subsequently, the evaluation is performed again and the process is continued until predefined parameters (eg material efficiency and cutting quality) are met.

[0043] In the following, the production of workpieces by means of a flatbed laser cutting machine is first explained and the production is set up with respect to a nesting plan ( Figure 1 and 2 ). Next, combine Figure 3 Describes the method used to generate nested plans.

[0044] exist Figure 1 The schematic flatbed machine tool 1 shown in FIG. 1 comprises a main housing 3 in which a cutting process is performed by means of a laser beam. The focus of the laser beam is guided by a control system, in particular, along a predetermined cutting line arranged in the processing area onto the material in order to cut a workpiece having a specific shape from the material, for example from a substantially two-dimensionally extending sheet material.

[0045] Furthermore, the flatbed machine tool 1 includes a pallet changer 5. The pallet changer 5 is configured to position one or more pallets during manufacturing. A material plate to be cut (as raw material or starting material) can be placed on the pallet 5A and then placed in the main housing 3 for the cutting process. After the cutting process is completed, the pallet can be replaced. Figure 1 As shown in FIG. 5 , the tray 5A with the cut material plate 7 can be carried out of the main housing 3 so that the cut workpieces 9 can be sorted out.

[0046] In the main housing 3, a laser processing head, from which the laser beam emerges, can be freely positioned in the processing region, so that the laser beam can be directed along essentially any two-dimensional cutting line on the material sheet to be cut. During laser cutting, the laser beam heats the metal along the cutting line until it melts. A gas jet, in most cases nitrogen or oxygen, usually emerges from the laser beam region of the laser processing head and pushes the molten material downwards and out of the constructed gap. As a result, during cutting, the material sheet 7 is completely cut through by the laser beam.

[0047] In order to cut out the workpiece 9, the laser beam is moved along the cutting line 10. This is usually done at a penetration point E located outside the workpiece 9 (see Figure 2 ) and then approaches the contour of the workpiece 9 in an arc (the so-called cut A). The point at which the cutting line first touches the contour of the workpiece is the point at which the cut is then ended (assuming a continuous cutting process). This point is called the pressure point D, because it is the point at which the emitted gas jet exerts pressure on the cut part, specifically at the time when it can first move freely. In particular in the case of thin sheet materials, the gas pressure can lead to a tilting of the workpiece, so that a part of the workpiece can protrude from the plane of the metal sheet and, for example, can collide with the cutting head.

[0048] The insertion point E and the pressure point D represent the reference points of the subspace in the planning area.

[0049] In the embodiment shown, the pallet 5A has a plurality of supporting webs 11, which extend transversely to the embedding direction and are oriented parallel to one another. For example, the supporting webs 11 have a spacing of 20 mm to 100 mm (e.g. 60 mm) between one another. The supporting webs 11 form a supporting area 11A, on which the material sheet 7 is placed. The supporting area 11A usually forms grid points, which can have a spacing of 5 mm to 50 mm (e.g. 15 mm) along the supporting webs 11, wherein the supporting webs have a thickness of 1 mm to 5 mm (e.g. 2 mm). Thus, the supporting area 11A forms a grid consisting of the following areas: these areas can influence the cutting process of the material sheet 7 located thereon. The area of ​​the supporting web that influences the cutting process can also extend to an area directly adjacent to the supporting area (which is in contact with the material sheet) (e.g. an edge of the supporting web 11 leading to the supporting area 11A).

[0050] When arranging subspaces 9A- 9F (corresponding to workpiece 9 ) in planning space 23 (corresponding to material plate 7 ), support webs 11 and in particular support regions 11A may be taken into account, for example in order to improve the quality of cut workpieces 9 or to reduce damage to support webs 11 .

[0051] Figure 1Also shown is a camera 13, which is arranged, for example, on the main housing 3. The camera 13 can be configured in particular for image detection of the relative positions of the pallet 5A, the supporting web 11 and the supporting area 11A, and the material plate 7 relative to the pallet 5A (and possibly the supporting web 11 and the supporting area 11A), and is connected to an image analysis processing unit of the control system of the flatbed machine tool 1.

[0052] The flatbed machine tool 1 can have a local manufacturing control system and / or a cloud-based manufacturing control system for executing the method described here. With the aid of the manufacturing control system, evaluations and nesting can be generated in real time during the operation of the flatbed machine tool 1. As a result, the flatbed machine tool can be provided with a nesting plan, for example, which is improved with respect to the cutting process, in particular shortly after the material panel has been placed.

[0053] In this context, "cloud-based" and "off-site data processing systems" refer to storage devices and / or data processing devices that are remote in location, preferably anonymized, in which data and evaluations from more than one user, advantageously from hundreds or thousands of different users, can be stored and / or processed computationally. As a result, different users can contribute to improving the method regardless of the manufacturing location. It has been recognized that the method only achieves decisive success when hundreds, especially thousands, especially tens of thousands, especially hundreds of thousands of user evaluations have been read. For a single manufacturing plant, such a volume of data is generally not reached within a year. Therefore, in some cases, the method may still be insignificant for such a manufacturing plant.

[0054] It can be seen that the cutting path on the web or the tilting of the workpiece 9 leads to damage at the support web 11 and / or at the workpiece 9 and / or at the cutting head and thus increases the risk of scrap and downtime. In addition, damage to the support web 11 leads to higher service costs for replacement or to longer downtimes. In the case of the removal of the support web 11 in the support area 11A, it is also possible to reduce the number of support points, which may increase the risk of tilting of the workpiece 9. If the cutting line 10 extends near the support area 11A, the risk of reduced quality of the underside of the workpiece, for example, increases. If the molten material cannot be blown out of the gap sufficiently and the workpiece cannot therefore be completely separated, the cutting process may also collapse, which may lead to more scrap parts.

[0055] Therefore, one task of the nesting method described here is also to propose an arrangement of the subspaces 9A-9F (corresponding to the workpieces 9 in the material plate 7) in the planning space 23 which reduces the aforementioned risks and possible additional costs caused by, for example, scrap parts, service and failure of the flatbed machine.

[0056] Figure 2A nested plan 21 (generally an arrangement of subspaces 9A-9F) is shown, which can be generated by an algorithm using an arrangement rule in a two-dimensional plan space 23. The arrangement rule can be a down (primary direction) - left (secondary direction) arrangement rule. Figure 2 , the main direction extends from right to left and the secondary direction extends from top to bottom. The planning space 23 is developed in the area of ​​the planning plate 25. The planning plate 25 is transferred to the material plate for the cutting process in such a way that the corresponding geometric shape data of the planning space 23 correspond to the processing area provided by the flatbed machine 1 to the material plate 7 (and the support situation corresponds to the assumed position data of the supported space). In the present example, a rectangular planning space 23 is assumed, which will be applied to a correspondingly rectangular shaped material plate. Other shapes are also conceivable.

[0057] The nesting plan 21 is created in a planning phase before the cutting process, for example by means of a control unit of the flatbed machine when, for example, detected current position data are taken into account in the planning, or in a separate planning unit with corresponding computing power if, for example, it is based on predetermined position data, which are then converted for the cutting process based on the corresponding positions of the material plate on the pallet and the supporting web. The creation of the nesting plan 21 can be part of a manufacturing control system.

[0058] The nesting plan 21 shows a non-overlapping arrangement of subspaces 9A to 9F in a two-dimensional planning space 23, wherein the (also two-dimensional) subspaces 9A to 9F correspond to six different types of workpieces. The nesting plan 21 here relates to the generation of, for example, 50 test workpieces.

[0059] The arrangement shown is based on an embedding sequence for a total of 50 subspaces. The embedding sequence generally determines the sequence in which the subspaces are successively embedded into the plan space 23 when nested plans 21 are continuously generated, and in which the subspaces are arranged in the plan space 23, for example, according to a bottom-left arrangement rule (strategy).

[0060] In the nesting plan 21, the spatial arrangement of the predetermined supported spaces 27 is also schematically maintained. In order to indicate the origin of the supported spaces, these are partially merged into lines in a manner similar to the supporting webs and are only shown locally as points in the region of the subspaces 9A to 9F. As already mentioned, the position data can be used in particular when evaluating the position of the subspaces 9A-9F.

[0061] For the sake of clarity, further cutting process data and cutting process parameters are shown in an enlarged section of a corner of the planning space 23. Each of the subspaces 9A-9F is bounded by one or more, in particular, closed contours. For example, an outer contour 31A and an inner contour 31B are indicated for the subspace 9A (highlighted by dashed lines). In addition, the insertion point E, the approach path A and the pressure point D are indicated with respect to the outer contour 31A' of the subspace 9B.

[0062] The exemplary subspaces also have different sizes, but are small enough, for example, so that the gas pressure caused by the laser cutting nozzle, for example, can affect the stability of the subspace. Figure 2 In the enlarged area of ​​, the individual supported spaces 27 in the subspace 9B can be seen, which together with the respective pressure points D and the respective centre of gravity S of the subspace define the susceptibility of the workpiece determined by the subspace 9B.

[0063] exist Figure 2 The nested plan 21 depicted in FIG. 2 is also based on a minimum workpiece spacing, which is determined in particular by the material thickness of the material sheet to be cut and the cutting parameters to be implemented. There is at least a minimum workpiece spacing between at least two adjacent subspaces 9A to 9F arranged in the planning space 23. The minimum workpiece spacing is, for example, in the range of 5 mm to 20 mm, in particular 10 mm.

[0064] For the nesting method described below, generally, an arrangement rule can be used, which defines how the subspaces are spatially arranged successively in the plan space. This is not limited to the bottom-left strategy based on the exemplary nesting plan shown in the accompanying drawings. Instead, for example, a bottom-left filling strategy or a non-fitting polygon scheme can also be adopted.

[0065] Reference Figure 3 In the flowchart of method 39 shown in the figure (the method is used to nest subspaces 9A-9F for controlling the cutting process of a flatbed machine tool 1 for cutting a workpiece 9 from a material plate 7), the nesting method proposed here generally proceeds from the following: there is an evaluation criterion for nesting, which can be implemented based on the representation of the subspaces in the planning space. The evaluation criterion relates, for example, to the overlap of geometric shapes, in particular the overlap of subspaces, but may also relate to the support space corresponding to the support of the material plate. In addition, the evaluation criterion may also relate to the angle of the accompanying beam interruption or the duration required for laser cutting taking into account thermal effects. For implementable evaluation criteria, see, for example, the German patent application mentioned at the beginning, application number 10 2018 124 146, entitled "Evaluation of workpiece positions in a nested arrangement".

[0066] In a first step 41 , evaluation criteria for the nesting are read in as a basis for evaluating the nesting result.

[0067] In step 43, sequence data 43' for nesting are generated. An exemplary method for this is also described in the German patent application No. 10 2018 124 146, entitled "Evaluation of workpiece positions in a nested arrangement", mentioned at the outset. In this case, the sequence data include data describing the complete nesting sequence. On the one hand, the sequence data are data defining the contours of the subspaces, i.e. the workpiece shape. In addition, the sequence data can include reference points of the subspaces, the order in which the cutting processes of individual subspaces and all subspaces are to be carried out, and the connection paths between the cutting processes.

[0068] In step 45, the sequence data 43' are evaluated within the scope of an evaluation algorithm 44 and evaluation data are generated for the sequence data 43'. The evaluation data relate to the evaluation criteria read in.

[0069] In step 47, result data 47' is generated by a combination logic of the evaluation data and the evaluation criteria, such as comparison, difference determination, ratio determination, and correlation calculation of the evaluation data and the evaluation criteria. The result data 47' may, for example, relate to improvement parameters such as material efficiency, workpiece quality, and damage rate.

[0070] In step 49, accounting data are generated from the sequence data 43', the evaluation data and the result data 47' by means of the evaluation algorithm 44. Accounting data are data for improving the nesting result (i.e. the evaluation data and / or the result data). The accounting data are incorporated into an aggregation, which is generally understood here to be a reorganization of data sets by means of an aggregation routine, as will be explained below with respect to the evaluation algorithm 44.

[0071] Taking into account the settlement data, new sequence data 43" are generated in step 51 with the aid of the evaluation algorithm 44. (It should be noted that step 43 and / or step 47 for generating the (initial) sequence data 43', i.e. generating result data, can already be implemented as part of the evaluation algorithm 44.) The settlement data can, for example, be incorporated into the generation of a new order of subspaces 9A, ... to be arranged, the settlement data setting new emphasis in the evaluation or making a specific order of the cutting process of a single subspace or all subspaces 9A, ... preferred.

[0072] When generating evaluation data, settlement data and / or other sequence data 43", an algorithm 44 including, for example, steps 45, 49 and 51 activates the execution of at least one data aggregation routine, which aggregates multiple input data into output data. The data aggregation routine itself can represent a small algorithm / subroutine that links multiple data of multiple data types to each other. Exemplary input data are, for example, sequence data read in by an evaluation algorithm, evaluation data generated by an evaluation algorithm and settlement data generated by an evaluation algorithm, output data of the same data aggregation routine and / or output data of another data aggregation routine. The input data includes at least two of the mentioned data types. Here, in some embodiments, the data aggregation routine can always be run with the aid of settlement data and at least one of the other mentioned data types of the input data. Output data are, for example, sequence data generated by an evaluation algorithm, evaluation data generated by an evaluation algorithm and settlement data generated by an evaluation algorithm.

[0073] In the evaluation algorithm 44, the settlement data can be assigned to other input data determined by the data aggregation routine and can be linked, in particular multiplied, with these input data. It is thus possible to determine which input data can have an influence, in particular a positive influence as much as possible, on the result data and / or the evaluation data. The settlement data corresponding to these input data are then adjusted in such a way that the linking (multiplication) of the settlement data corresponding to the input data leads to output data that influences the result, in particular as positively as possible, and the result can be continuously improved. However, at the same time, the influence of the settlement data on other evaluation data and / or result data can also be determined and, if necessary, the settlement data can be readjusted accordingly.

[0074] As in Figure 3 As described in , steps 45 to 51 are repeated multiple times and a plurality of result data 47 ′, 47 ″ are generated accordingly for a plurality of sequence data 43 ′, 43 ″. This can be continued until the result data exceeds a range or a maximum number predefined with respect to the evaluation criterion.

[0075] Then, in step 53 , the arrangement of the subspaces to be implemented for the cutting process and the implementation of the cutting sequence are derived from the sequence data 43 ″ generated up to that point as a result of the method for nesting the subspaces. This includes the cutting plan 25 , on the basis of which the control of the flatbed machine to produce a workpiece corresponding to the subspace should be based.

[0076] In other words, the method described here can be used to generate nesting results with the aid of a genetic algorithm. The efficiency of the nesting results can then be evaluated by a neural network and the next evolutionary stage of the genetic algorithm can be driven on this basis. The method ends when a predetermined criterion (e.g. material efficiency) is reached. Thus, it is possible to go back and forth between nesting and path improvement / optimization. This can be achieved, for example, as follows:

[0077] In a first step, a genetic sequence representing the nesting result is generated. To this end, (placement) rules (such as bottom-left placement) are applied in order to create an initial nesting result of sufficient quality. In the first step, configuration parameters such as web width can also be specified, but this is purely optional.

[0078] In a second step, a neural network (e.g., Kohonen characteristic diagram) is used to evaluate the quality of the nesting result. In this case, the output neurons can be represented by reference points of the part (e.g., shown as polygonal columns), wherein the connection of the output neurons is determined by abnormal situations (e.g., by overlapping of geometric shapes, angles with beam interruptions, or the duration required for laser cutting while taking into account thermal effects).

[0079] In the third step, the output of the neural network is used to perform a resequencing of the gene sequence, which is then used in the genetic algorithm. Next, the classification is performed again by the neural network. The method continues until the pre-given optimization parameters (such as material efficiency, quality, etc.) are met.

[0080] It is explicitly emphasized that for the purpose of original disclosure and for the purpose of limiting the claimed invention, all features disclosed in the description and / or claims are to be considered independent and mutually independent, regardless of the feature combination in the embodiments and / or claims. It is explicitly pointed out that for the purpose of original disclosure and for the purpose of limiting the claimed invention, all range descriptions or descriptions of groups of units disclose every possible intermediate value or subgroup of units, in particular also as a limitation of the range description.

Claims

1. A method (39) for nesting subspaces (9A-9F), wherein: The subspace (9A-9F) is arranged in a two-dimensional planning space (23) and is bounded by a contour line in the two-dimensional planning space (23), wherein the subspace (9A-9F) is configured to control a cutting process of a flatbed machine tool (1) so as to cut a workpiece (9) from a material plate (7) along at least one cutting line, the cutting line corresponding to the contour line of the subspace (9A-9F), and the method comprises the following steps: a. Read in (step 41) the evaluation criteria for the arrangement of the nested subspaces (9A-9F); b. generating (step 43) sequence data (43') for the arrangement of the nested subspaces (9A-9F); c. generating (step 45) evaluation data by evaluating the sequence data (43') by means of an evaluation algorithm (44); d. generating (step 47) result data (47') based on the combination logic of the evaluation data and the evaluation criteria; e. generating (step 49) settlement data from the sequence data (43'), the evaluation data and the result data (47') by means of the evaluation algorithm (44); f. generating (step 51) further sequence data (43") by means of the evaluation algorithm (44) taking into account the settlement data; and g. Repeat steps c to f until the result data (47', 47") exceeds the predetermined range, The evaluation algorithm (44) implements at least one data aggregation routine when generating evaluation data, settlement data and / or other sequence data (43"), wherein the data aggregation routine i. Aggregate multiple input data into output data when it is activated, ii. wherein the input data has at least two of the following data types: The sequence data (43', 43") read in by the evaluation algorithm, The evaluation data generated by the evaluation algorithm, The settlement data generated by the evaluation algorithm, the output data of another data aggregation routine, and output data from a previous run of the same data aggregation routine, iii. wherein the output data affects at least one of the following data types: sequence data (43") generated by said evaluation algorithm, evaluation data generated by the evaluation algorithm, and Settlement data generated by the evaluation algorithm.

2. The method (39) according to claim 1, wherein: The evaluation criteria include variables corresponding to the arrangement of the subspaces and characterizing the overlap of the subspaces (9A-9F), the relative angles of the segments of the contour line that may trigger a beam interruption during the cutting process and / or the duration of the cutting process, and In this case, the evaluation criterion can be at least partially predefined by a user or, alternatively or additionally, can be at least partially predefined by a control device.

3. The method (39) according to claim 1 or 2, wherein: The sequence data (43', 43") includes the following data: the data describes a nested sequence of subspaces in the planning space (23), the nested sequence including a predetermined number of subspaces (9A-9F), wherein the data includes the contours of the subspaces (9A-9F) and the cutting order of the contours of the subspaces (9A-9F).

4. The method (39) according to claim 2, wherein: The evaluation data represents an evaluation of a variable corresponding to the evaluation criterion.

5. The method (39) according to claim 1 or 2, wherein: The result data includes data defining improvement parameters and defining the quality of the workpiece produced, and The combinational logic includes the following steps: the steps are to perform comparison, difference determination, ratio determination and / or correlation determination between the evaluation data and the evaluation criteria.

6. The method (39) according to claim 1 or 2, wherein: corresponding the settlement data to determined input data of the data aggregation routine and linking the settlement data with the input data, and The settlement data includes the following data: the data is constructed to improve the arrangement of the nested subspaces (9A-9F).

7. The method (39) of claim 6, wherein: The settlement data include data which can be used to determine which input data have an influence on the result data and / or the evaluation data.

8. The method (39) according to claim 1 or 2, wherein: The evaluation algorithm (44) executes the at least one data aggregation routine multiple times and, in doing so, assigns output data of another data aggregation routine or output data of a previously executed data aggregation routine to the data aggregation routine at least once as input data.

9. The method (39) according to claim 1 or 2, wherein: The data aggregation routine is configured to link multiple data of multiple data types to each other, and / or, The input data include settlement data generated by the evaluation algorithm (44) and additionally include The sequence data (43', 43"), The evaluation data, Output data from another data aggregation routine and / or Output data from the same data aggregation routine, and / or Therein, the at least one data aggregation routine is designed to link the settlement data with another data type.

10. The method (39) of claim 2, wherein: The variable characterizes the duration of the cutting process taking into account thermal effects.

11. The method (39) of claim 2, wherein: The control device is a superior control device.

12. The method (39) of claim 3, wherein: The data include connection paths between reference points and / or contour lines of the subspace (9A-9F).

13. The method (39) of claim 5, wherein: The result data includes data defining the material efficiency of the arrangement of the subspaces (9A-9F).

14. The method (39) of claim 6, wherein: The settlement data is multiplied by the input data.

15. The method (39) of claim 6, wherein: The settlement data include data which are designed to improve the corresponding evaluation data and / or result data (47', 47").

16. The method (39) of claim 7, wherein: The settlement data include data that can be used to determine which input data have the most positive possible influence on result data and / or evaluation data, so that the settlement data corresponding to the input data can then be adjusted in such a way that the linking of the settlement data corresponding to the input data causes the output data to influence the result as positively as possible, thereby enabling the result to be continuously improved.

17. The method (39) of claim 16, wherein: The linking of the settlement data corresponding to the input data comprises multiplication.

18. The method (39) of claim 7, wherein: The influence of the settlement data on other evaluation data and / or result data (47', 47") is determined.

19. The method (39) of claim 8, wherein: The evaluation algorithm (44) executes the at least one data aggregation routine more than ten times.

20. The method (39) of claim 8, wherein: The evaluation algorithm (44) executes the at least one data aggregation routine more than one hundred times.

21. The method (39) of claim 8, wherein: The evaluation algorithm (44) executes the at least one data aggregation routine more than one thousand times.

22. The method (39) of claim 8, wherein: The evaluation algorithm (44) executes the at least one data aggregation routine more than ten thousand times.

23. The method (39) of claim 9, wherein: The at least one data aggregation routine is designed to multiply the settlement data with another data type.

24. A manufacturing system, comprising: A flatbed machine tool (1) for cutting workpieces (9) from a material plate (7) according to a workpiece-specific cutting contour, and An off-site data processing system and / or a local manufacturing control system, wherein the off-site data processing system and / or the local manufacturing control system is configured to implement the method (39) according to any one of claims 1 to 23 so as to determine the arrangement of the subspaces (9A-9F), and to output the arrangement of the subspaces (9A-9F) as a control signal to the flatbed machine tool (1) so as to cut a workpiece corresponding to the subspaces (9A-9F) from the material plate (7).

25. The manufacturing system of claim 24, wherein: The off-site data processing system comprises a computing device, a control device and / or a storage device, in which evaluation data and / or result data (47', 47") are generated and stored for a plurality of sequence data (43', 43").

26. The manufacturing system according to claim 24 or 25, wherein: The flat machine tool (1) is configured to process flat objects.

27. The manufacturing system of claim 25, wherein: The off-site data processing system includes computing devices, control devices, and / or storage devices that are remote in location.

28. The manufacturing system of claim 25, wherein: The off-site data processing system includes an anonymized computing device, a control device and / or a storage device.

29. The manufacturing system of claim 25, wherein: In the computing device, control device and / or storage device, evaluation data and / or result data (47', 47") are generated and stored by different users for a plurality of sequence data (43', 43").

30. The manufacturing system of claim 25, wherein: Evaluation data and / or result data (47', 47") are generated and stored anonymously in the computing device, control device and / or storage device for a plurality of sequence data (43', 43").

31. The manufacturing system of claim 25, wherein: In the computing device, the control device and / or the storage device, evaluation data and / or result data (47', 47") are generated and stored for hundreds or thousands of different sequence data nested at one time.

32. The manufacturing system of claim 26, wherein: The flatbed machine tool (1) is configured to process bending-resistant objects.

33. The manufacturing system of claim 26, wherein: The flatbed machine tool (1) is configured to be used for processing sheet metal plates.

34. The manufacturing system of claim 26, wherein: The flatbed machine tool is configured as a laser processing machine.

35. The manufacturing system of claim 26, wherein: The flatbed machine tool is configured as a laser cutting machine.

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