Method for simulating a coating facility and corresponding coating facility

Abstract

The present invention relates to a method for simulating a coating installation, comprising the following steps: a) specifying geometric data of the parts to be coated; b) specifying general coating parameters; c) specifying initial values ​​of the coating parameters to be optimized, including a coating path and a current spray pattern for each path point of the coating path, the current spray pattern representing the coating thickness distribution on the part around the paint impact point on the part; d) for each path point of the coating path, program-controlled execution of the following steps in a simulation loop: calculation of a simulated coating result by computer superimposition of the current spray pattern provided for each path point of the coating path, taking into account the degree of wetting; testing of the simulated coating result, taking into account the degree of wetting; adjustment of the coating parameters to be optimized and repeating the simulation loop if the simulated coating result is not satisfactory; termination of the simulation loop if the simulated coating result is satisfactory and adoption of the optimized coating parameters.

Description

[Technical field]

[0001] The present invention relates to a method for simulating a coating installation for coating parts by means of applicators, in particular a painting installation for painting automotive body parts by means of sprayers or printheads. The present invention also relates to a corresponding coating installation for carrying out the simulation method. [Background technology]

[0002] US Pat. No. 5,399,433 and US Pat. No. 5,499,443 disclose simulation methods that allow for the simulation of painting processes.

[0003] In this process, geometric data reflecting the shape of the part to be painted is first specified, for example this may be specified in the form of a Computer Aided Design (CAD) file, which represents the shape of the vehicle body to be painted.

[0004] Additionally, general painting parameters such as the air temperature in the paint booth or paint parameters (eg, paint viscosity) are also specified.

[0005] In addition, the paint impingement point of the applicator (eg, rotary sprayer) used dictates the paint path to be followed during operation.

[0006] Furthermore, initial values ​​of the coating parameters to be optimized are defined, which may be the so-called current spray patterns, i.e. the layer thickness distribution around the respective paint impact points. These current spray patterns are superimposed as part of the simulation.

[0007] Within the scope of the present invention, this computer-generated superimposition of the current spray pattern can also be performed using a projection method, i.e., the spray pattern (which can be adapted with respect to certain aspects of the coating situation) is geometrically projected onto the workpiece shape. The current spray pattern projected onto the workpiece shape is then superimposed. Thus, the term superimposing the current spray pattern as used in the context of the present invention also includes the above-mentioned projection methods.

[0008] The current spray pattern can then be optimized within the simulation loop to achieve the best possible coating result in the simulation. For example, one goal of the optimization can be to achieve the most uniform film thickness possible.

[0009] The current spray pattern used in the simulation of the coating process can be derived from reference spray patterns stored in a database for various reference coating situations. As part of the simulation loop, the current coating situation is first determined for each path point of the coating path. Then, a reference spray pattern measured in a reference painting situation that is as close as possible to the actual current painting situation is read out from the database. However, as a rule, the database does not contain reference spray patterns corresponding to all possible current painting situations. Therefore, in practice, it is intended that the current spray pattern is determined by interpolation or mathematical adaptation of the reference spray patterns stored in the database.

[0010] The known simulation method described above already provides satisfactory simulation results. However, there is a need to further optimize the known simulation method. [Prior art documents] [Patent documents]

[0011] [Patent Document 1] DE 102019113341 A1 [Patent Document 2] DE 102020114201 Summary of the Invention [Problem to be solved by the invention]

[0012] The invention is therefore based on the problem of creating a correspondingly improved simulation process. Furthermore, the invention is based on the problem of creating a correspondingly adapted coating installation that is suitable for carrying out the simulation process according to the invention. [Means for solving the problem]

[0013] This problem is solved by a simulation method according to claim 1 and a coating installation according to the dependent claims.

[0014] The invention is based on the newly acquired technological and physical knowledge that the quality of a coating does not only depend on the uniformity of the coating thickness. Rather, the quality of the coating is also determined by the so-called degree of wetting. In the simulation, multiple current spray patterns are superimposed and the simulated coating consists of the superposition of multiple current spray patterns. Similarly, the real coating on the real part also has multiple overlaps, which originate from multiple spray patterns applied to the part surface along, for example, parallel coating paths.

[0015] It is also possible that the various overlaps of the current spray patterns each contribute equally to the overall layer thickness. For example, if three current spray patterns are overlapped at one point on the part surface, each current spray pattern may contribute one-third to the overall coating thickness. However, it is also possible that the various overlaps of the current spray patterns contribute significantly differently to the overall layer thickness. For example, in a triple overlap, each overlap may contribute in the ratio of 70%:20%:10% to the overall layer thickness. In the context of the present invention, the degree of wetting may reflect the percentage of the total coating thickness contributed by each overlapping layer. For example, the degree of wetting may indicate the one with the largest percentage of overlap in the total coating thickness.

[0016] In addition, the number of overlaps of different layers may vary across the coated part surface. For example, a coating at one location on the part surface may be composed of three overlapping layers of the current spray pattern, while a coating at another location on the part surface may be composed of five overlapping layers of the current spray pattern. The term "wetting degree" as used in the context of the present invention may refer to the number of overlapping layers of the current spray pattern that make up the coating at each point on the part surface.

[0017] Additionally, the degree of wetting also reflects the geometric characteristics of the current spray pattern, which affects the total layer thickness at each point on the part surface.

[0018] Furthermore, within the scope of the present invention, it is also possible for the degree of wetting to indicate the height of the total layer thickness at each point on the component surface.

[0019] The term "wettability" as used in the context of the present invention may reflect one or more of the above definitions.

[0020] When determining the degree of wetting, within the scope of the present invention, some or all locally relevant spray patterns (e.g. average values ​​of percentages, ratios of percentages, ...) or only one specific locally relevant spray pattern (e.g. the one that results in the highest degree of wetting at the location under consideration, the one that is overcoated last, ...) can be taken into account.

[0021] It should be mentioned here that when calculating the simulated coating result, a different current spray pattern may be used than when calculating the wetting degree.

[0022] The simulation method according to the invention is preferably suitable for a paint installation for painting automotive body parts using sprayers (e.g. rotary sprayers) or printheads. However, the invention is not limited to use in paint installations and can also be implemented in connection with coating installations that apply other coatings such as adhesives, insulating materials or sealants, to name just a few.

[0023] Additionally, the present invention is not limited to use in paint facilities that paint automotive body parts, and therefore, with respect to the parts that are coated, the present invention is not limited to automotive body parts.

[0024] Furthermore, the present invention is not only suitable for simulation in coating installations that use atomizers (e.g. rotary atomizers) or printheads as applicators, but the principles according to the invention are also generally applicable in this respect.

[0025] The simulation method according to the invention first provides that geometric data reflecting the geometry of the part to be coated are specified according to the known simulation method mentioned above. For example, these geometric data can be read from a part file in the form of CAD data (CAD: Computer Aided Design) of the part to be coated. Alternatively, it is also possible to generate the geometric data of the part to be coated by measuring the real part.

[0026] Furthermore, the simulation method according to the invention also provides that general coating parameters are initially specified, such as coating agent parameters (e.g. viscosity), applicator type, bell cup type or path spacing of adjacent coating paths, according to the known simulation method described at the beginning. These general coating parameters are preferably specified by a user or read from a data memory. It should be mentioned here that these general coating parameters do not have to be optimized as part of the simulation process according to the invention. However, it is also possible within the scope of the invention to optimize the general coating parameters as well.

[0027] In addition, initial values ​​of the coating parameters to be optimized are defined. As known per se from the prior art, the coating parameters to be optimized initially constitute a coating path consisting of a number of path points that are traced by the paint impact points of an applicator (e.g. a rotary sprayer) in the coating process. It should be noted here that the term "path point" should be generally understood in the context of the present invention and preferably refers to a temporal or spatial discretization of the path trajectory (e.g. one path point every x milliseconds or one path point every y millimeters).

[0028] In addition, the optimized coating parameters also include a so-called current spray pattern for each path point of the coating path, whereby the current spray pattern reflects the coating thickness distribution on the part around the paint impact point on the part.

[0029] It should be mentioned here that the initial values ​​of the coating parameters to be optimized do not have to be specified by the user but can be defined by the program, e.g., as known from the prior art, the initial values ​​of the current spray pattern can be derived from reference spray patterns already determined for various coating situations, e.g. by means of coating test sheets.

[0030] The simulation method according to the invention provides for program-controlled execution of a number of steps in a simulation loop, whereby each step is performed for each path point of the coating path.

[0031] First, a simulated coating result is calculated as part of the simulation loop by superimposing the actual current spray pattern for each point of the coating path, which may also be performed using a projection method, for example, as described in more detail below.

[0032] In the simulation loop, the simulation results are checked in the next step, e.g. the uniformity of the obtained layer thickness is evaluated as a quality parameter. However, the invention is characterized in that the degree of wetting at each point of the component surface is determined and taken into account as a quality parameter.

[0033] The next step in the simulation loop is to adjust the coating parameters to be optimized (eg, current spray pattern, coating path) to optimize the simulated coating result.

[0034] The simulation loop is repeated until the simulated coating results are satisfactory and the degree of wetting at each point on the component surface determined during the simulation is also acceptable.

[0035] The above procedure is restated below in different words to avoid misunderstanding. The user can assign different (or the same) reference spray patterns to different path sections. For the first simulation run, these will be the initial values ​​specified by the user (e.g. brush table with the width of the spray pattern and a scaling factor for the height of the spray pattern). Depending on the painting situation of the workpiece, these reference spray patterns are automatically adapted by the program to create the current spray pattern, which is used for the simulation. For the first simulation run, the initial values ​​can be those automatically determined by the program based on the reference spray patterns specified by the user and the painting situation of the workpiece. If the first simulation result is not satisfactory, the user changes the assignment of the reference spray patterns (e.g. wider spray pattern, higher spray pattern, ...), i.e. changes the initial values ​​from the first simulation run. Subsequently, the automatically defined current spray pattern used for the simulation is also changed. This continues until a satisfactory coating thickness result is achieved.

[0036] It has already been mentioned that the coating parameters to be optimized (e.g. current spray pattern, coating path) are optimized as part of the simulation loop. This optimization can be done, for example, based on the operator's experience. In a preferred embodiment, however, the coating parameters to be optimized are adjusted in the simulation loop using artificial intelligence (AI).

[0037] At the start of the simulation loop, an initial value of the current spray pattern at each point of the coating path is specified. When determining the current spray pattern, the respective current coating situation is preferably taken into account. For example, the current coating situation is characterized by the coating distance (i.e., the distance between the applicator and the part surface), the part geometry at the paint impact point, and similar coating parameters. Depending on this current coating situation at each path point of the painting path, the associated current spray pattern can be determined with the aid of a spray pattern database in which reference spray patterns for different coating situations are stored.

[0038] For example, the stored reference spray patterns may be determined in a spray pattern test in which a test sheet is coated with different reference coating regimes. The coating thickness distribution on the test sheet is then measured and stored in the spray pattern database together with the associated coating parameters defining the respective reference coating regime. The current spray pattern may be derived from the stored reference spray patterns, e.g., by interpolating the various stored reference spray patterns. For example, if the current coating regime does not exactly correspond to the reference coating regime of the reference spray patterns stored in the spray pattern database, two or more reference spray patterns determined for similar coating regimes may be interpolated.

[0039] However, the current spray pattern does not necessarily have to be determined by interpolation from a plurality of stored reference spray patterns. Instead, it is also possible to determine the current spray pattern by mathematically adjusting the stored reference spray patterns. This adaptation of the reference spray patterns stored in the database according to the current coating situation can also be performed, for example, by an algorithm using artificial intelligence (AI).

[0040] In practice, when the current coating situation is a geometric edge (e.g., a coating path on the edge of a workpiece), an adjustment can be automatically made using a correction or scaling factor, since a certain percentage of the coating agent beam (projection beam) passes through the workpiece, and the adjusted spray pattern can be projected onto the workpiece surface.

[0041] The current coating regime and the reference coating regime can be defined, for example, by at least one of the following variables: Applicator type, Bell cup type of rotary sprayer forming applicator, The type of shaping air ring used in the applicator; Application parameters, especially - Flow rate of coating agent, Shaping air volume, Bell cup speed, High voltage for electrostatic coating agent charging system, The spatial orientation of the applicator axis of the applicator relative to the surface of the part to be coated, · absolute spatial orientation of the applicator axis in space, Booth parameters of the coating booth, especially Booth temperature in the coating booth, -Downstream wind speed in the coating booth, · pass distance between adjacent coating passes, the path speed at which the applicator moves along the coating path; The coating path used to measure the reference spray pattern, · Coating path in the current coating situation; The geometry of the test part used to measure the reference spray pattern; The geometry of the part to be coated.

[0042] It has been mentioned above that the reference spray patterns stored in the spray pattern database can be determined by coating tests on test sheets prior to the simulation loop. The coating thickness distributions measured on the test sheets are stored in the spray pattern database as reference spray patterns assigned to the respective reference coating situations.

[0043] It should also be mentioned that the reference spray patterns stored in the spray pattern database can be either dynamic or static spray patterns. A dynamic spray pattern is measured as a result of a coating process in which the applicator moves relative to the part (e.g., a test sheet). On the other hand, a static spray pattern is measured as a result of a coating process in which the applicator is stationary relative to the part (e.g., a test sheet).

[0044] In the simulation loop, it is possible to continuously check at which points of the coating path the adjustment of the coating parameters to be optimized has led to a change of the coating parameters. This means that in the various runs of the simulation loop, the coating parameters are not usually changed at all path points. The simulation only needs to be updated at those path points where the optimization of the coating parameters has actually caused a change. Thus, in the context of the present invention, the simulation loop does not have to cover all path points of the coating path in each run.

[0045] Furthermore, it should be mentioned that the general coating parameters mentioned above may include at least one of the following variables: - the coating properties of the coating material, in particular the viscosity of the coating material; Applicator type, Rotary sprayer bell cup type, Booth parameters of the coating booth, especially Booth temperature in the coating booth, -Downstream wind speed in the coating booth, The desired coating thickness of the coating agent on the component, · pass distance between adjacent coating passes, ·Path speed at which the applicator moves along the application path.

[0046] The coating parameters that are optimized may include, for example, at least one of the following variables: the spatial course of the coating path, in particular the coordinates of each path point, the spatial orientation of the applicator axis of the applicator at each point of the coating path; Brush parameters, especially - Flow of coating agent, Shaping air flow, - Voltage of electrostatic coating agent charging system, Switch-on points of applicators on the coating path, Switch-off points of applicators on the coating path, the flow of the coating material at each point in the coating path; the atomizer velocity at each path point of the coating path; High voltage for electrostatic coating agent charging system, - Applicator type, especially for sealing applications · pass distance between adjacent coating passes, the path speed at which the applicator moves along the application path; General coating parameters above.

[0047] In the context of the present invention, the simulated coating result may be displayed graphically on a screen to allow an operator to make an easy evaluation, however, it is also possible for the simulated coating result to be evaluated automatically, for example by artificial intelligence (AI).

[0048] After the simulation process according to the present invention is completed, optimized coating parameters are available for each path point of the coating path. These optimized coating parameters are transferred to the control system of the coating equipment, which controls the coating equipment in the actual coating operation. In practice, the optimized coating parameters are converted into actual control variables for controlling the coating equipment.

[0049] This conversion of the optimized coating parameters into real control variables for controlling a coating installation ("forward conversion") preferably relates to the commissioning or optimization of an existing system or an existing coating. However, within the scope of the present invention, it is also possible to have the existing control variables of the coating installation loaded into the simulation computer and converted into an initial parameterization of the simulation. As initial values ​​of the coating parameters to be optimized, control variables for controlling a coating installation that have already been tested in real conditions are used here ("back conversion"). The term "conversion of the optimized coating parameters into real control variables for controlling a coating installation" as used in the context of the present invention is therefore to be understood as a general term.

[0050] It should further be mentioned that the present invention does not claim protection only for the simulation method according to the invention described above. Rather, the present invention also claims protection for a corresponding coating installation suitable for carrying out the simulation method according to the invention. In addition to at least one coating robot with an applicator (e.g. a rotary sprayer) and a control system, the coating installation according to the invention also comprises a simulation computer on which a simulation program is stored, which executes the simulation method according to the invention when executed.

[0051] Typically, the simulation can be performed on an "offline" computer (e.g. an office laptop) (e.g. in a planning department, an offline department, a training department, ...) and the discovered coating parameters can be transferred to a control system, e.g. at a later time / if necessary.

[0052] Further advantageous embodiments of the invention are characterized in the dependent claims or are explained in more detail below with reference to the drawings together with the description of preferred embodiments of the invention. [Brief description of the drawings]

[0053] [Figure 1A] 4 is a flow chart illustrating a simulation process according to the present invention. [Figure 1B] 4 is a flow chart illustrating a simulation process according to the present invention. [Diagram 2] (Figure 2A) Schematic of the overlap of three current spray patterns applied to three parallel coating passes. (Figure 2B) Shows the layer thickness resulting from the overlap of the three current spray patterns. (Figure 2C) Shows the number of overlaps of the current spray patterns at different points on the part surface. (Figure 2D) Shows the progression of the degree of wetting at different points on the part surface. [Diagram 3] (FIG. 3A) A coating with three overlaps of the current spray pattern that contribute significantly to the overall coating thickness. (FIG. 3B) A variation of FIG. 3A, where each overlap contributes equally to the overall coating thickness. [Figure 4] FIG. 4A shows a reference spray pattern measured in a reference coating regime. FIG. 4B shows a corresponding current spray pattern in a modified current coating regime, where the current spray pattern was derived from the reference spray pattern in FIG. 4A. [Diagram 5] 1 is a simplified schematic diagram of a painting installation according to the present invention having a simulation computer for carrying out a simulation process according to the present invention; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0054] The flow chart shown in Figures 1A and 1B illustrating in simplified form a simulation method in accordance with the present invention is now described.

[0055] In a first step S1, a file containing a definition of the shape of the car body to be painted is first read in. For example, this file can be provided as a CAD file by the respective car manufacturer.

[0056] In a further step S2, general painting parameters are set, such as the following painting parameters: -Painting route distance, Route speed, - paint properties of the paint used, Sprayer type, - Booth temperature of spray booth, Downdraft speed in spray booth.

[0057] In a further step S3, initial values ​​of the painting parameters to be optimized are specified under program control for the subsequent simulation run. For example, the painting parameters to be optimized can be the following painting parameters: -Painting route course, - Switch-on and switch-off points of the sprayers along the coating path; - the orientation of the sprayer axis at various points along the coating path; Brush parameterization, e.g. paint flow, air flow shape, voltage of high voltage electrostatic charging system.

[0058] After the first run of the simulation loop, the painting parameters to be optimized for the next simulation run are adjusted in step S4, which can be done, for example, by operator experience or by artificial intelligence (AI).

[0059] In the next step S5, path points of the robot path at which adjustments of the optimized painting parameters led to a significant change in the painting situation are determined, which is useful because the simulation loop, which will be described in detail below, does not have to include all path points of the robot path, including path points at which adjustments of the optimized painting parameters did not lead to a significant change in the painting situation.

[0060] In the next steps S6, S7 and S8, a simulation loop is performed over all path points of the coating path where the coating parameters have been significantly changed.

[0061] A first step S6 provides that a current spray pattern is determined depending on the respective current painting situation at the individual path points. For example, reference spray patterns can be retrieved for this purpose from a spray pattern database. These reference spray patterns can be predetermined, for example, by means of coating test sheets. When determining the current spray pattern corresponding to the respective current painting situation, it is first checked whether a reference spray pattern measured in a reference painting situation that exactly corresponds to the current painting situation is stored in the spray pattern database. If so, the stored reference spray pattern can be retrieved and accepted as the current spray pattern.

[0062] However, this is usually not possible. Instead, in practice, the current spray pattern is computationally derived from one or more stored reference spray patterns measured in similar reference coating situations. This adaptation of the stored reference spray patterns to determine the current spray pattern used according to step S7 can be performed, for example, using artificial intelligence (AI). For example, as already mentioned, projection methods can also be used.

[0063] In the next step S8, the painting result including the degree of wetting is simulated based on the following variables: The current spray pattern for each individual path point of the paint path, General coating parameters, - Body shape, Optimized coating parameters.

[0064] The next step S9 verifies whether the simulated painting result is satisfactory, if not, the optimized painting parameters are adjusted again for the next simulation run in step S4.

[0065] Otherwise, the optimized painting parameters are stored in the next step S10 and can be used to control the painting equipment in the actual painting operation.

[0066] FIG. 2A shows an example of three current spray patterns 1, 2, 3 applied by a rotary sprayer while traversing three parallel portions of a coating path, the current spray patterns 1-3 partially overlapping on the part surface 4. The current spray patterns 1-3 are shown in the form of highly simplified trapezoids. However, in reality, the current spray patterns 1-3 have slightly different shapes depending on the type of application device used. Therefore, the schematic representation of the current spray patterns 1-3 is only intended to serve to explain the invention.

[0067] 2B shows the resulting layer thickness SD for various points on the part surface perpendicular to the path portion of the coating path. From this figure, it can be seen that the layer thickness SD is completely constant for optimal overlap of adjacent current spray patterns 1-3, which is an optimal condition and cannot be achieved in practice.

[0068] 2C also shows that the current spray patterns 1-3 result in coatings consisting of different numbers of overlaps due to their overlapping. For example, the coating between x=x2 and x=x3 consists of n=2 overlaps, and the coating between x=x3 and x=x4 consists of a single overlap (n=1). It should be noted that this example is merely theoretical and is intended to illustrate the invention.

[0069] Finally, FIG. 2D shows the progression of possible wetting degrees N G along the part surface across the path sections of the coating path, where N is the desired number of overlaps n TARGET = 2, i.e., if possible, the coating should consist of n = 2 overlaps of the current spray patterns 1-3 at each point on the part surface. The degree of wetting NG at each point on the part surface is then defined as the difference from this target value. Thus, the coating between x = x3 and x = x4 is composed only of the current spray pattern 2, with the desired number of overlaps n TARGET The difference from x=x2 is NG=1. However, between x=x2 and x=x3, the coating consists of the superposition of the two current spray patterns 1, 2, and the wetting degree NG as the difference from the desired value is NG=0.

[0070] In the diagrams according to FIGS. 2A-2D, the wetting degree NG only indicates how many superimposed layers of the current spray pattern 1-3 the coating consists of at each point on the part surface.

[0071] However, the degree of wetting can also indicate what percentage of the total coating thickness each individual layer of the current spray pattern makes up. Figures 3A and 3B show a coating 5 having a total layer thickness SD, which is composed of three overlaps 6-8 of the current spray pattern. In Figure 3A, overlap 6 makes up a majority of the total layer thickness SD, resulting in a correspondingly greater degree of wetting. On the other hand, in Figure 3B, overlaps 6-8 each make up an equal third of the total layer thickness SD, resulting in a correspondingly lower degree of wetting.

[0072] 4A shows diagrammatically a reference spray pattern 9 on a part surface 10, which was applied and measured in a reference coating situation. The reference coating situation was characterized, among other things, by the fact that the applicator axis was arranged perpendicular to the part surface 10.

[0073] On the other hand, Fig. 4B shows a current painting situation in which the applicator axis is arranged at an angle to the part surface 10. The difference between the reference painting situation according to Fig. 4A and the current painting situation according to Fig. 4B leads to a corresponding adapted current spray pattern 11. This adaptation of the stored reference spray pattern 9 to determine a current spray pattern 11 suitable for the simulation can be performed, for example, using artificial intelligence (AI). For example, as already mentioned, correction methods or projection methods can also be used.

[0074] The schematic diagram shown in Figure 5 is explained below. Firstly, the diagram shows in highly simplified form a conventional painting installation 12 controlled by a control computer 13.

[0075] Additionally, there is shown a simulation computer 14 which is used to carry out the simulation method according to the invention. For this purpose, the simulation computer 14 is connected to a database computer 15 which stores a spray pattern database in which reference spray patterns are stored.

[0076] On the input side, the simulation computer 14 first receives the geometric data of the vehicle body to be painted.

[0077] In addition, the simulation computer 14 also receives general painting parameters as input.

[0078] Additionally, the simulation computer 14 receives at its input initial values ​​for the painting parameters to be optimized. These initial values ​​may include, for example, the painting path and the current spray pattern for each point of the painting path.

[0079] The simulation computer 14 transmits each current painting situation to the database computer 15, which determines a preferred current spray pattern corresponding to each current painting situation, typically by fitting or interpolating stored reference spray patterns. The database computer 15 provides the preferred current spray patterns for each path point of the painting path to the simulation computer 14. The simulation computer 14, together with the database computer 15, may thus execute the simulation process shown in Figures 1A and 1B.

[0080] The present invention is not limited to the preferred embodiments described above. Rather, there are numerous variants and modifications that utilize the inventive concept and are therefore within the scope of protection. In particular, the present invention also claims protection for the subject matter and features of the dependent claims, independently of the claims referred to in each case, and in particular also with the exception of the features of the main claim. The present invention includes various aspects of the invention which enjoy protection independently of each other. In particular, the following aspects of the invention which may enjoy protection independently of each other are mentioned: The aspect of "wetting", i.e. taking into account the wetting degree as a quality parameter for evaluating simulated painting results. - The aspect of "adaptation of the reference spray pattern to the current painting situation".

[0081] (Additional Note) (Appendix 1) 1. A simulation method for a coating installation (12) for coating parts by means of an applicator, in particular for painting automotive body parts by means of a sprayer or a printhead, comprising the steps of: a) specifying geometric data reproducing the shape of the part to be coated, in particular a1) by retrieving the shape data of the part to be coated from a part file; or a2) by measuring the part to be coated and generating said shape data upon measuring the part to be coated; b) specifying general coating parameters; c) specifying initial values ​​for coating parameters to be optimized, including: c1) a coating path traversed by said applicator during a coating process, said path being comprised of a plurality of path points; and c2) current spray patterns (1-3; 11) for individual path points of a coating path, said current spray patterns (1-3; 11) reproducing a coating thickness distribution on said part around a coating agent impact point on said part, and initial values ​​of said current spray patterns (1-3; 11) are preferably derived in a program-controlled manner from reference spray patterns (9) determined for different reference coating situations; d) program-controlled execution of the following steps in a simulation loop for each of the path points of the coating path: d1) calculation of a simulated coating result, in particular the coating thickness of the coating on the part, by computer superposition of the current spray pattern (1-3; 11) provided to the individual path points of the coating path; d2) Verification of simulated coating results; d3) optimizing said coating parameters, in particular adjusting said current spray pattern (1-3; 11) and / or said coating path, and repeating said simulation loop if said simulated coating result is not satisfactory; d4) if the simulated coating result is satisfactory, terminating the simulation loop and adopting optimized coating parameters; e) during the calculation of the simulated coating result in the simulation loop, the degree of wetting of the simulated coating on the part is calculated for various points of the part surface (4;10), said degree of wetting being: e1) how many superimposed layers (6-8) of the current spray pattern (1-3; 11) the coating consists of at each point of said component surface (4; 10), and / or e2) what percentage of the total layer thickness (SD) of the coating does each individual superimposed layer (6-8) of the current spray pattern (1-3; 11) represent at each point on said component surface (4; 10); and / or e3) which geometrical characteristics of the current spray pattern affect the total layer thickness (SD) at each point of the component surface (4; 10); and / or e4) how high the total layer thickness (SD) is at each point of the component surface (4;10), A simulation method comprising:

[0082] (Appendix 2) a) in case of unsatisfactory coating results, adjustments of the coating parameters optimized in the simulation loop are carried out by an operator on the basis of experience, or b) in case of unsatisfactory coating results, the adjustment of the coating parameters optimized in the simulation loop is carried out by artificial intelligence; 2. The simulation method according to claim 1,

[0083] (Appendix 3) The following steps are performed to determine the current spray pattern (1-3; 11) to be used in the simulation loop at each path point of the coating path to simulate a coating result: a) determining a current coating situation at each path point of the coating path, the current coating situation being defined by the shape data, the coating parameters to be optimized and the general coating parameters; and b) determining the current spray pattern (1-3; 11) corresponding to the current coating situation, in particular b1) by retrieving said current spray patterns (1-3; 11) for each said path point according to the respective current coating situation from a spray pattern database (15) in which reference spray patterns (9) for various reference coating situations are stored, or b2) by calculating said current spray pattern (1-3; 11) according to said current coating situation from a predefined reference spray pattern (9) which reproduces a reference coating situation, 3. The simulation method according to claim 1 or 2, comprising:

[0084] (Appendix 4) determining the current spray pattern (1-3; 11) to be used at each path point of the coating path, the following steps: a) determining the current coating status at each of the path points of the coating path; b) determining the designated reference coating regime on which the reference spray pattern retrieved from the spray pattern database (15) is based; c) comparing the current coating regime with the reference coating regime and determining a difference between the current coating regime and the reference coating regime; d) adapting the reference spray pattern (9) retrieved from the spray pattern database (15) depending on the difference between the current coating situation and the reference coating situation; 4. A simulation method according to claim 3, comprising:

[0085] (Appendix 5) a) the adaptation of the reference spray pattern (9) retrieved from the spray pattern database (15) is carried out according to the current coating situation by means of an algorithm, in particular an artificial intelligence algorithm; and / or b) the reference spray pattern (9) retrieved from the spray pattern database (15) is adapted by a correction or scaling factor in order for a certain percentage of the coating agent jet to bypass the workpiece, especially when the current coating situation is a geometric edge. 5. A simulation method according to claim 4.

[0086] (Appendix 6) The current coating regime and the reference coating regime are determined by the following variables: a) the coating properties of the coating agent, in particular the viscosity; b) the type of applicator; c) the type of bell cup of the rotary atomizer forming said applicator; d) the type of shaping air ring used in said applicator; e) application parameters, in particular e1) coating agent flow rate; e2) Shaping air volume, e3) the velocity of said bell cup; e4) High voltages in electrostatic coating agent charging systems; f) the spatial orientation of the applicator axis of said applicator relative to the surface of the part to be coated; g) the absolute spatial orientation of the applicator axis in space; h) Booth parameters of the coating booth, in particular: h1) the booth temperature in said coating booth; h2) the downward wind speed in said coating booth; i) the path distance between adjacent coating paths; j) a path speed at which the applicator moves along the coating path; k) the coating path used to measure said reference spray pattern (9); l) the coating path for said current coating situation; m) the geometry of the test part used to measure said reference spray pattern (9); n) the shape of the part to be coated; defined by at least one of 6. A simulation method according to any one of claims 3 to 5.

[0087] (Appendix 7) a) the reference spray pattern (9) stored in the spray pattern database (15) is determined by a coating test prior to the simulation loop; b) during said coating test the test sheets are coated with different coating regimes; c) measuring the coating thickness distribution on the test sheet during the coating test; d) storing the coating thickness distributions measured on the test sheets in the spray pattern database (15) as reference spray patterns assigned to the respective reference coating situations; 7. A simulation method according to any one of claims 3 to 6.

[0088] (Appendix 8) a) the reference spray pattern (9) stored in the spray pattern database (15) is a dynamic spray pattern measured as a result of a coating process in which the applicator moves relative to the part, and / or b) the reference spray pattern (9) stored in the spray pattern database (15) is a static spray pattern measured as a result of a coating process in which the applicator is stationary relative to the part; 8. A simulation method according to any one of claims 3 to 7.

[0089] (Appendix 9) a) identifying, in the simulation loop, the path points of the coating path at which adaptation of the coating parameter to be optimized led to a change in the coating parameter; b) in the simulation loop, the simulated coating result is recalculated entirely or as a difference to a previously simulated coating result only in the region of the path points of the coating path where the adjustment of the coating parameters to be optimized led to a change of the coating parameters, 9. A simulation method according to any one of claims 1 to 8.

[0090] (Appendix 10) Typical coating parameters include the following variables: a) the coating properties of the coating agent, in particular the viscosity of said coating agent; b) the type of applicator; c) the type of bell cup of the rotary atomizer forming said applicator; d) Booth parameters of the coating booth, in particular: d1) the booth temperature in said coating booth; d2) the downward wind speed in said coating booth; e) a desired coating thickness of said coating material on said component; f) the path distance between adjacent coating paths; g) the path speed at which the applicator moves along the coating path; 10. A simulation method according to any one of claims 1 to 9, comprising at least one of the following:

[0091] (Appendix 11) The coating parameters to be optimized are the following variables: a) the spatial and / or temporal course of said coating path, in particular the coordinates and / or times of the individual said path points, b) the spatial orientation of the applicator axis of the applicator at each point of said coating path; c) brush parameters, in particular the flow of the coating material; d) the switch-on point of the applicator on the coating path; e) switch-off points of the applicators on the coating path; f) the flow of coating material at said individual points of said coating path; g) atomizer velocity at said individual points of said coating path; h) High voltages in electrostatic coating agent charging systems; i) the type of applicator, especially for sealing applications; j) the path distance between adjacent coating paths; k) the path speed at which the applicator moves along the coating path; l) General coating parameters as given in Appendix 10; 11. A simulation method according to any one of claims 1 to 10, comprising at least one of the following:

[0092] (Appendix 12) In the context of verifying the simulated coating results in said simulation loop, the following steps are performed: a) displaying the simulated coating results graphically on a screen and evaluating them by an operator; or b) performing an automated evaluation of the simulated coating results by artificial intelligence; 12. A simulation method according to any one of claims 1 to 11, comprising:

[0093] (Appendix 13) a) transmitting simulated coating parameters to a control system of the coating equipment after the simulation loop is completed; b) said control system (13) controls the coating installation according to said transmitted coating parameters, in particular by converting said coating parameters into control variables of the coating installation; 13. A simulation method according to any one of claims 1 to 12.

[0094] (Appendix 14) A coating installation for coating parts, in particular for painting automotive body parts, comprising: a) at least one coating robot; b) at least one applicator guided by said coating robot; c) a control system (13) for controlling said applicator and said coating robot; Equipped with d) a simulation computer (14) having a simulation program stored therein, which, when executed, performs the simulation method according to any one of claims 1 to 13; The coating equipment is characterized by: [Explanation of symbols]

[0095] 1-3 Current spray pattern 4. Part surface 5. Coating 6-8 Overlap of individual current spray patterns 9 Reference Spray Pattern 10 Component Surface 11 Current spray pattern 12 Painting equipment 13 Control computer 14 Simulation Computer 15. A database computer having a database of reference spray patterns. SD Total layer thickness

Claims

1. 1. A simulation method for a coating installation (12) for coating parts by applicators, in particular for painting automotive body parts by sprayers or printheads, comprising the following steps: a) specifying geometric data reproducing the shape of the part to be coated, in particular a1) by retrieving the shape data of the part to be coated from a part file; or a2) by measuring the part to be coated and generating said shape data upon measuring the part to be coated; b) specifying general coating parameters; c) specifying initial values ​​for coating parameters to be optimized, including: c1) a coating path traversed by said applicator during a coating process, said path being comprised of a plurality of path points; and c2) current spray patterns (1-3; 11) for individual path points of the coating path, said current spray patterns (1-3; 11) reproducing a coating thickness distribution on said part around a coating agent impact point on said part, and initial values ​​of said current spray patterns (1-3; 11) preferably derived in a program-controlled manner from reference spray patterns (9) determined for different reference coating situations; d) program-controlled execution of the following steps in a simulation loop for each of the path points of the coating path: d1) calculation of the simulated coating result, in particular the coating thickness of the coating on the part, by computer superposition of the current spray pattern (1-3; 11) provided at the individual path points of the coating path; d2) Verification of simulated coating results; d3) optimizing the coating parameters, in particular adjusting the current spray pattern (1-3; 11) and / or the coating path, and repeating the simulation loop if the simulated coating result is not satisfactory; d4) if the simulated coating results are satisfactory, terminating the simulation loop and adopting optimized coating parameters; e) during the calculation of the simulated coating result in the simulation loop, the degree of wetting of the simulated coating on the part is calculated for various points of the part surface (4; 10), said degree of wetting being: e1) how many superimposed layers (6-8) of the current spray pattern (1-3; 11) the coating consists of at each point on the surface of the component (4; 10), and / or e2) what percentage of the total layer thickness (SD) of the coating does each superimposed layer (6-8) of the current spray pattern (1-3; 11) represent at each point on the component surface (4; 10); and / or e3) which geometrical characteristics of the current spray pattern affect the total layer thickness (SD) at each point of the component surface (4; 10); and / or e4) how high the total layer thickness (SD) is at each point on the component surface (4; 10), A simulation method comprising:

2. a) In the event of an unsatisfactory coating result, adjustments of the coating parameters optimized in the simulation loop are carried out empirically by the operator, or b) In the event of an unsatisfactory coating result, the adjustment of the coating parameters optimized in the simulation loop is carried out by artificial intelligence; The simulation method according to claim 1 ,

3. The following steps are performed to determine the current spray pattern (1-3; 11) to be used in the simulation loop at each path point of the coating path to simulate the coating result: a) determining a current coating situation at each path point of the coating path, the current coating situation being defined by the shape data, the coating parameters to be optimized, and the general coating parameters; and b) determining the current spray pattern (1-3; 11) corresponding to the current coating situation, in particular b1) by retrieving the current spray patterns (1-3; 11) for the individual path points according to the respective current coating situation from a spray pattern database (15) in which reference spray patterns (9) for various reference coating situations are stored, or b2) by calculating said current spray pattern (1-3; 11) according to said current coating situation from a predetermined reference spray pattern (9) that reproduces a reference coating situation, The simulation method according to claim 1 or 2, comprising:

4. determining the current spray pattern (1-3; 11) to be used at each path point of the coating path, by: a) determining the current coating status at each of the path points of the coating path; b) determining the designated reference coating regime on which the reference spray pattern retrieved from the spray pattern database (15) is based; c) comparing the current coating regime with the reference coating regime and determining a difference between the current coating regime and the reference coating regime; d) adapting said reference spray pattern (9) retrieved from said spray pattern database (15) depending on the difference between said current coating situation and said reference coating situation; The simulation method according to claim 3, comprising:

5. a) the adaptation of the reference spray pattern (9) retrieved from the spray pattern database (15) is carried out according to the current coating situation by an algorithm, in particular an artificial intelligence algorithm; and / or b) the reference spray pattern (9) retrieved from the spray pattern database (15) is adapted by a correction or scaling factor in order to allow a certain proportion of the coating agent jet to bypass the workpiece, especially when the current coating situation is a geometric edge; 5. The simulation method according to claim 4, wherein:

6. The current coating situation and the reference coating situation are determined by the following variables: a) the coating properties of the coating agent, in particular the viscosity; b) the type of applicator; c) the type of bell cup of the rotary atomizer forming said applicator; d) the type of shaping air ring used in said applicator; e) application parameters, in particular e1) coating agent flow rate; e2) Shaping air volume, e3) the velocity of the bell cup; e4) High voltage of electrostatic coating agent charging system; f) the spatial orientation of the applicator axis of said applicator relative to the surface of the part to be coated; g) the absolute spatial orientation of the applicator axis in space; h) booth parameters of the coating booth, in particular h1) booth temperature within said coating booth; h2) the downward wind speed in the coating booth; i) the path distance between adjacent coating paths; j) the path speed at which the applicator moves along the coating path; k) the coating path used to measure said reference spray pattern (9); l) the coating path for the current coating situation; m) the geometry of the test part used to measure the reference spray pattern (9); n) the shape of the part to be coated; defined by at least one of 4. The simulation method according to claim 3, wherein:

7. a) the reference spray pattern (9) stored in the spray pattern database (15) is determined by a coating test prior to the simulation loop; b) during said coating test, the test sheets are coated with different coating regimes; c) measuring the coating thickness distribution on the test sheet during the coating test; d) the coating thickness distribution measured on the test sheet is stored in the spray pattern database (15) as a reference spray pattern assigned to each reference coating situation; 4. The simulation method according to claim 3, wherein:

8. a) the reference spray pattern (9) stored in the spray pattern database (15) is a dynamic spray pattern measured as a result of a coating process in which the applicator moves relative to the part; and / or b) the reference spray pattern (9) stored in the spray pattern database (15) is a static spray pattern measured as a result of a coating process in which the applicator is stationary relative to the part; 4. The simulation method according to claim 3, wherein:

9. a) identifying, in the simulation loop, the path points of the coating path at which adaptation of the coating parameters to be optimized led to changes in the coating parameters; b) in the simulation loop, the simulated coating result is recalculated entirely or as a difference from the previously simulated coating result only in the region of the path points of the coating path where the adjustment of the coating parameters to be optimized led to a change in the coating parameters; 3. The simulation method according to claim 1, wherein the simulation method comprises:

10. Typical coating parameters include the following variables: a) the coating properties of the coating agent, in particular the viscosity of said coating agent; b) the type of applicator; c) the type of bell cup of the rotary atomizer forming said applicator; d) booth parameters of the coating booth, in particular: d1) the booth temperature within said coating booth; d2) the downward wind speed in the coating booth; e) the desired coating thickness of the coating on the part; f) the path distance between adjacent coating paths; g) the path speed at which the applicator moves along the coating path; 3. The simulation method according to claim 1, further comprising at least one of the steps of:

11. The coating parameters to be optimized are the following variables: a) the spatial and / or temporal course of the coating path, in particular the coordinates and / or times of the individual path points, b) the spatial orientation of the applicator axis of the applicator at each point of the coating path; c) brush parameters, in particular the flow of the coating material; d) the switch-on point of the applicator on the coating path; e) the switch-off point of the applicator on the coating path; f) the flow of coating material at each point of the coating path; g) atomizer velocity at each point in the coating path; h) High voltage of electrostatic coating agent charging system; i) the type of applicator, especially for sealing applications; j) the path distance between adjacent coating paths; k) the path speed at which the applicator moves along the coating path; l) the general coating parameters of claim 10; 3. The simulation method according to claim 1, further comprising at least one of the steps of:

12. In the context of verifying the simulated coating results in the simulation loop, the following steps: a) graphically displaying the simulated coating results on a screen for evaluation by an operator; or b) automated evaluation of the simulated coating results by artificial intelligence; 3. The simulation method according to claim 1, further comprising:

13. a) transmitting the simulated coating parameters to a control system of the coating equipment after the simulation loop is completed; b) said control system (13) controls the coating equipment according to said transmitted coating parameters, in particular by converting said coating parameters into control variables of the coating equipment; 3. The simulation method according to claim 1, wherein the simulation method comprises:

14. 1. A coating installation for coating parts, in particular for painting automotive body parts, comprising: a) at least one coating robot; b) at least one applicator guided by said coating robot; c) a control system (13) for controlling the applicator and the coating robot; Equipped with d) a simulation computer (14) having a stored simulation program which, when executed, performs the simulation method according to claim 1 or 2; Coating equipment characterized by:

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