Programming method for a spraying device and corresponding spraying device

Abstract

The invention relates to a method for programming a process-controlled spraying device for spraying components with a spraying robot and an application device, in particular for programming a painting device for painting motor vehicle body components with a painting robot, having the following steps (S1 - S3): a) specifying or determining the geometric data of the component to be sprayed (S1); b) specifying the robot path data to be followed by the robot path (S2); c) determining suitable spray pattern data (S3), which reflects the layer thickness distribution and is determined by a simulation taking into account the robot path data and the geometric data of the component to be sprayed. The invention also includes a corresponding suitable spraying device.

Description

Field of the Invention

[0001] The present invention relates to a method for programming a programmatically controlled spraying device, in particular a painting device for painting motor vehicle body components. Background Art

[0002] In modern painting devices for motor vehicle body components, rotary atomizers are generally used as application devices, which are guided by multi-axis painting robots to the motor vehicle body components to be painted. The operation of the painting device and the control of the painting robot and the rotary atomizer are all programmatically controlled. Therefore, before actual painting operations, the painting device must be programmed. As part of the programming, the paths of the robot are planned offline, which will be traversed by the paint landing points of the rotary atomizer, taking into account predefined painting specifications such as specified path spacing and path speed. In addition, during programming, application parameters of the rotary atomizer are defined, such as paint flow rate, speed, shaping air flow, etc., and these application parameters are defined according to predefined painting specifications and based on the experience of professionals. The purpose of programming is, among other things, to achieve the most uniform spray thickness distribution on the component to be sprayed. Therefore, during programming, by changing the application parameters and the robot paths, based on the painting tests on the test vehicle body, the spray thickness distribution is optimized in multiple iterative cycles. The disadvantage of this well-known programming method is the high cost in terms of time, painting materials, and test vehicle bodies.

[0003] On the other hand, in newer development lines, which have not been put into practice yet, attempts are being made to fully physically simulate the painting process, so that the optimization of the robot paths and the application parameters can be carried out as part of the simulation. However, the disadvantage of this new development line is that a large amount of computational work is required within the simulation framework, and thus the time required for the calculation is not yet practically feasible.

[0004] Regarding the general technical background of the present invention, reference should also be made to US2012 / 0156362A1 and DE19651716A1. Summary of the Invention

[0005] Therefore, the task of the present invention is to create an improved method for programming a programmatically controlled spraying device. In addition, the present invention is also based on the task of creating a corresponding adaptable spraying device.

[0006] This task is solved by the method according to the present invention or the spraying device according to the present invention of the independent claims.

[0007] The programming method according to the invention first provides available geometric data which represents the geometric features of the component to be sprayed (e.g. a motor vehicle body component). Within the scope of the programming method according to the invention, the geometric data can be measured, for example, on the basis of the real component, or can be specified, for example, in the form of a file.

[0008] Furthermore, the programming method according to the invention also specifies robot path data which defines the robot path that the application device guided by the spraying robot traverses during the spraying operation at the paint landing point (TCP: tool center point).

[0009] It should be mentioned here that with regard to the type of application device, the invention is not limited to the rotary atomizer mentioned at the beginning. Instead, the application device can also be a print head which, in contrast to an atomizer, does not emit a spray jet of coating agent but emits a spatially limited jet of coating agent. Alternatively, within the scope of the invention, the application device can also be a airless atomizer or an air-mixed atomizer, just to mention a few additional examples here.

[0010] Furthermore, the programming method according to the invention provides determinable spray pattern data, also referred to as "brush curve", which represents the layer thickness distribution, in particular the three-dimensional layer thickness distribution, that is generated by the application device on the surface of the component around the paint landing point during the actual spraying operation. For example, a rotary atomizer, when spraying an idealized flat component surface, generates a rotationally symmetric, doughnut-shaped spray thickness distribution. The spray pattern data can then reflect the course of the spray thickness as a function of the radial distance from the paint landing point. For example, the three-dimensional spray thickness distribution (static spray pattern) can be converted into a two-dimensional spray thickness distribution (dynamic spray pattern) from which the spray pattern data can be determined, for example, when generating a characteristic map. However, within the scope of the invention, the spray pattern data can also represent a dynamic spray pattern, for example the layer thickness cross-section along the spraying path.

[0011] In the context of the invention, the spraying result is simulated on the basis of the spray pattern data and the spray pattern data is optimized on this basis until an acceptable spraying result is simulated. The acceptable spray pattern data is then stored in a first data set in order to subsequently determine suitable application parameters (e.g. paint flow rate, shaping air flow, rotational speed of the rotary atomizer, etc.) which are suitable for implementing the previously determined spray pattern data in practice.

[0012] However, it may happen that for a given robot path, even the most suitable spray pattern data does not result in an acceptable spraying result. In this case, not only the spray pattern data but also the robot path needs to be optimized. Therefore, in an embodiment of the present invention, it is checked whether the spraying result simulated with the most suitable spray pattern data leads to an acceptable spraying result. If so, there is no need to optimize the robot path, and the most suitable spray pattern data determined in the simulation can be continued to be used. Otherwise, the robot path is optimized, and the most suitable spray pattern data is determined iteratively during the simulation until the simulated spraying result is acceptable.

[0013] When optimizing the robot path, the following optimization measures can be carried out, for example:

[0014] - Adjust the path route, for example, change the polygonal route defining the path route,

[0015] - Adjust the distance of the path,

[0016] - Shorten or extend the path (e.g., at the edges),

[0017] - Introduce additional paths,

[0018] - Remove paths,

[0019] - Adjust the direction of the applicator axis on the robot path,

[0020] - Adjust the path speed,

[0021] - Change the start or end points on the robot path, especially at the edges, path reversal points, interfaces (spray module connections) of the spraying areas of different spraying robots.

[0022] - Optimize the spray width or diameter, spray shape, and the ratio of the paint flow rate through brush parameterization, and optimize by inserting or deleting brush numbers through relevant brush parameterization.

[0023] During the simulation for determining the suitable spray pattern data, the characteristics of the atomizer and / or the bell cup shaping air ring system are preferably also taken into account, especially in terms of the possible paint flow rate and the achievable spray pattern width.

[0024] However, in addition to the spray pattern data, other data can also be optimized as part of the simulation. For example, the robot path sequence and the start / stop points of the paint flow can also be optimized.

[0025] The programming method according to the present invention also provides a simulation of the spraying result, as in the case of the prior art described at the beginning. However, in the spraying method according to the present invention, no physical simulation is carried out, and such a simulation is much more complex. Instead, the simulation according to the present invention is based on the spraying pattern data and the spraying thickness distribution defined thereby, so the simulation according to the present invention is much simpler and can therefore also be carried out within a feasible calculation time.

[0026] As already mentioned above, after the simulation, suitable spraying pattern data (brush curve) can be obtained in the first data set. However, such spraying pattern data is not yet suitable for controlling the application device. Therefore, in the programming method according to the present invention, it is preferably to determine suitable application parameters (such as the rotational speed of a rotary atomizer, the paint flow rate, the shaping air flow, etc.) from the determined suitable spraying pattern data, which are suitable in actual operation for achieving the previously determined suitable spraying pattern data when the application device moves along the specified robot path. Then, these suitable application parameters are stored in the second data set.

[0027] Then the spraying device can be operated with the application parameters determined in this way. When operating with the previously determined application parameters, the previously determined suitable spraying pattern data will be applied in practice, which are determined to be suitable based on the simulation and result in an acceptable spraying result.

[0028] In a variant of the present invention, the suitable spraying pattern data is determined on the side of the spraying device operator during the simulation, for example, it can be done automatically or with the intervention of an assisting user. Then, the first data set with the suitable spraying pattern data determined during the simulation is transferred from the operator side to the side of the spraying device manufacturer, for example, to a service provider commissioned by the spraying device manufacturer. Then, the service provider uses the suitable spraying pattern data transmitted by the spraying device operator to determine suitable application parameters based on the characteristic map and transmits these parameters back to the spraying device operator, who then operates the spraying device with the transmitted application parameters.

[0029] In another variant of the invention, the determination of suitable spray pattern data within the simulation framework is also carried out at the operator of the spraying device, in particular automatically or with the intervention of an assisted user. The operator of the spraying device then receives a characteristic map for determining suitable application parameters, which is created on the manufacturer's side, for example by a service provider commissioned by the spraying device manufacturer. For example, the operator of the spraying device can transmit spraying data to the service provider, specifying the coating agent to be used. Then, the service provider commissioned by the manufacturer can select or create a suitable specific spraying characteristic map and transmit it to the operator of the spraying device. Then, the operator of the spraying device determines suitable application parameters from the suitable spray pattern data according to the characteristic map previously transmitted by the manufacturer.

[0030] As already mentioned above, the first data set contains suitable spray pattern data, which led to an acceptable spraying result in the simulation. In addition, the first data set with suitable spray pattern data can also contain other spraying data. For example, the following data can be included in the first data set:

[0031] - The ideal spray thickness of the coating agent layer on the component surface. This preferably refers to the spray thickness in the dry state, rather than the spray thickness of the wet paint,

[0032] - A coating agent identifier for identifying the coating agent and / or coating agent properties. For example, the coating agent identifier can indicate what solid components the coating agent used contains, or whether it is a primer or a varnish,

[0033] - An application device identifier for identifying the application device and / or application device properties. For example, the application device identifier can indicate which type of rotary atomizer is used,

[0034] - In addition, the spraying data can also include layer information to distinguish different layers in multi-layer spraying,

[0035] - Another example of possible spraying data is the path speed of the paint landing point along the robot path, which also affects the spraying result.

[0036] When determining the suitable application parameters mentioned above, it is then preferably not only necessary to take into account the spray pattern data contained in the first data set, but also the spraying coating data mentioned above. In addition, reference values for the path distance, path speed, target layer thickness, solid content of the coating agent, and application efficiency of the application device between adjacent spraying paths can also be taken into account.

[0037] As already mentioned above, robot path data is taken into account in the simulation, and the robot path data defines the robot path that the paint landing point of the application device has to traverse during the spraying operation. These robot path data preferably include the following data:

[0038] - The spatial route of the robot path,

[0039] - The path velocity of the paint landing point along the robot path,

[0040] - The path distance between laterally adjacent, laterally overlapping or adjacent path portions in the robot path,

[0041] - The direction of the application device,

[0042] - The time route of the paint landing point along the robot path or the velocity of the paint landing point along the robot path,

[0043] - The opening point and / or closing point of the paint flow, and / or

[0044] - The number of the active brush. Which brush number is active with respect to the corresponding brush parameterization in the robot path?

[0045] Furthermore, it should be mentioned that the robot path is preferably divided into a plurality of successive path segments, which will be successively traversed by the paint landing points of the application device. Then, the suitable spray pattern data is preferably determined individually and specifically for each path segment of the robot path. In addition, the suitable application parameters can also be determined individually and specifically for each path segment.

[0046] As already mentioned above, the determination of the suitable spray pattern data (brush curve) is carried out in a simulation. In a preferred embodiment of the invention, this simulation includes a plurality of iterative steps, which are run one after the other, and each step contains an optimization loop.

[0047] In the first optimization step, it is preferably to specify default values for the spray pattern and the coating agent flow rate, especially in the form of percentages, relative values or virtual values (reference brush). These default values only serve as starting values for the simulation spraying results. During the subsequent simulation based on the specified default values, it is preferably to determine the spray thickness distribution and determine the deviation of the simulated spray thickness distribution from the target. Regarding the spray thickness uniformity of the surface of a large component, the robot path data can already be optimized in this first optimization step.

[0048] The initial values of the above-mentioned simulation can include, for example, a reference value for the path distance between the central axes of directly adjacent spray paths. For example, when spraying a motor vehicle body, the spray paths are usually applied to the motor vehicle body, and the spray paths are parallel to each other and laterally overlapping. Therefore, the starting value of the simulation can also define the lateral overlap of directly adjacent spray paths. In addition, the starting value of the simulation can also include a reference value for the coating agent flow rate.

[0049] In the second optimization step, the test of the spray diameter uniformity is preferably carried out at the simple module joints. The surface of the component to be sprayed is usually divided into spray modules, which are sprayed one by one. For example, the spray modules can be the hood, roof, trunk lid, fenders and doors of a motor vehicle body, and they are sprayed one by one. In this case, adjacent modules are joined to each other at the module boundary. In the sense of the present invention, a simple module joint refers to the boundary between adjacent modules, where exactly two adjacent spray modules are joined to each other. For example, in a motor vehicle body, the front side door and the rear side door can each form a spray module, so the boundary between the front door and the side door forms a simple module joint. On the other hand, the joint between three or more adjacent spray modules is called a complex module joint in the context of the present invention. For example, such a complex module joint occurs where the engine hood, fenders, front door and A-pillar are adjacent on a motor vehicle body.

[0050] In the second optimization step, first, the layer thickness uniformity at the above-mentioned simple module joints is determined and compared with the target value. In the second optimization step, then the robot path can be optimized to optimize the layer thickness uniformity at the simple module joints. This optimization can be completed in multiple iteration cycles, which run continuously until an acceptable improvement in the layer thickness uniformity is achieved.

[0051] In the third optimization step, the layer thickness uniformity can be optimized at the above-mentioned complex module joints. Here, the robot path can also be adjusted multiple times in the third optimization step to optimize the layer thickness uniformity at the complex module joints. In the third optimization step, this optimization can be carried out in multiple optimization cycles, which run one by one until an acceptable layer thickness uniformity is achieved at the complex module joints.

[0052] In the fourth optimization step, the layer thickness uniformity at the simple and / or complex module joints can be optimized again. However, in the fourth optimization step, it is not the robot path that is adjusted, but the spray pattern data (brush curve) and / or the flow rate of the coating agent. The optimization in the fourth optimization step can also be carried out in multiple optimization cycles, which run one by one until the simulation results in an acceptable spraying result at the simple or complex module joints.

[0053] Finally, in a fifth optimization step, the spray thickness uniformity at the edges of the component to be sprayed can be optimized. For example, the component edge can be the edge of the engine hood to be sprayed or the edge of the door of the motor vehicle body to be sprayed. In the fifth optimization step, the spray thickness uniformity at the component edge is simulated and compared with a specified target value for the spray thickness uniformity. Then, the robot path, the spray pattern data, and / or the coating agent flow rate can be adjusted until an acceptable spraying result is obtained from the simulation. In the fifth optimization step, the following adjustments can be made, for example:

[0054] - Optimize the robot path: Adjust the path, for example, make general modifications to a polygonal path, or adjust, shorten, and extend the path in terms of path distance (e.g., at the edge), add paths, reduce paths, adjust the direction of the bell plate axis, adjust the speed,

[0055] - Optimize by changing the opening and / or closing points of the coating flow (GUN ON / GUN OFF), especially at the edge, path transition points, interfaces between spraying areas of different robots (spraying module connections),

[0056] - Optimize the spray width or spray diameter, spray shape, and the ratio of the coating flow rate through brush parameterization, and optimize by inserting or deleting the brush numbers related to the brush parameterization.

[0057] It should be mentioned here that the above adjustments (positioning bolts) can be made not only within the framework of the fifth optimization step but also generally. The optimization in the fifth optimization step can also be carried out in multiple optimization cycles that run one after another until the simulation results in an acceptable spraying result at the component edge.

[0058] As part of the spray result simulation, the spray result can also be graphically displayed on the operator's screen. For example, the component to be sprayed can be displayed as a perspective model on the screen. The surface of the displayed component model to be sprayed can be colored according to the position, whereby the color of the component surface on the screen reflects, for example, the local deviation between the simulated coating spray thickness and the specified target value of the spray thickness. This visualization of the simulated spray result on the screen provides the programmer with a quick and intuitive overview of the simulated spray result.

[0059] As mentioned above, after determining the appropriate spray pattern data (brush curve), the appropriate application parameters suitable for implementing the specified spray pattern data are determined as part of the simulation. This conversion is preferably carried out on the basis of a multi-dimensional characteristic map. For example, the following several variables of a specific spraying medium can be related.

[0060] - The width of the spray thickness distribution, in particular the SB50 value of the spray thickness distribution. The SB50 value here refers to the width of the spray thickness distribution, where the spray thickness is at least 50% of the maximum spray thickness.

[0061] - The shaping air flow of the application device (such as a rotary atomizer).

[0062] - The coating agent flow rate of the application device (such as a rotary atomizer).

[0063] - The rotational speed of the rotary atomizer as the application device.

[0064] - The high voltage of the electrostatic coating agent charge.

[0065] - The path speed of the application device (such as a rotary atomizer) along the robot path.

[0066] - The spray distance between the application device and the surface of the component to be sprayed.

[0067] As mentioned above, the robot path data is specified, which determines the orientation of the robot path during the actual spraying operation. For example, this robot path data can be specified by the operator based on the geometric data of the component to be sprayed. Additionally, the robot path data can also be provided by the manufacturer and then read in by the spray equipment operator in the form of a file.

[0068] The same situation also applies to the geometric data of the component to be sprayed. For example, these data can be determined by the spray equipment operator on the operator's side as part of the measurement process. However, in another case, the geometric data can be provided by the manufacturer.

[0069] It has also been shown in practice that regarding the simulation method and the spray pattern data of the spray mode, it is beneficial to be able to at least partially avoid spray jet deformation, such as deformation at the edges, A-pillars, etc. Therefore, special painting situations and influences, such as air flow in the spray booth, air flow around the atomizer and around the workpiece, high voltage effects, etc., will be automatically taken into account in the simulation if necessary, for example, considering the geometric features of the workpiece edges, the grooves of the skylight, or complex workpieces.

[0070] In addition, it should be mentioned that the present invention does not only claim protection for the above-described programming method according to the present invention. On the contrary, the present invention also claims protection for the corresponding spray equipment suitable for executing the programming method according to the present invention.

[0071] According to the state of the art, the spray equipment according to the present invention initially includes at least one spray robot, at least one application device (such as a rotary atomizer), and a controller for controlling the application device and the spray robot. In the spray equipment according to the present invention, the controller is designed to execute the programming method according to the present invention.

[0072] For example, the above-mentioned characteristic map can be stored in the controller to determine appropriate application parameters from suitable spraying pattern data.

[0073] Furthermore, the spraying device according to the invention preferably has a data interface for transmitting spraying pattern data and / or spraying data to the spraying device manufacturer or a service provider commissioned by it, and for receiving from the spraying device manufacturer or the service provider relevant characteristic maps for determining appropriate application parameters. Description of the Drawings

[0074] Other advantageous embodiments of the invention are indicated in the dependent claims or are explained in more detail below in connection with the description of the preferred embodiments of the invention with reference to the drawings.

[0075] Figure 1A 、 1B shows a flowchart illustrating a programming method according to the invention;

[0076] Figure 2 shows a flowchart for simulating a spraying result in the programming method according to the invention;

[0077] Figure 3 shows an example of the spraying thickness distribution generated by a rotary atomizer;

[0078] Figure 4 shows different spraying thickness distributions generated with the variation of the paint flow rate;

[0079] Figure 5 shows an example of a characteristic map that connects spraying pattern data on the one hand and application parameters on the other hand;

[0080] Figure 6 shows a schematic diagram of a spraying device according to the invention;

[0081] Figure 7 shows Figure 1A modifications of Detailed Description of the Invention

[0082] According to Figure 1A and 1B the flowcharts of

[0083] which illustrate the programming method according to the invention, will now be described as follows.

[0084] In a first step S1, geometric data are first specified, which reflect the geometric characteristics of the component to be sprayed (e.g., a motor vehicle body component). For example, these geometric data can be provided in the form of a file and can be easily read out. Alternatively, the geometric data can also be measured with a real component.

[0084] In a second step S2, robot path data is provided which defines the movement path of the paint landing points of the application device on the surface of the component. The robot path data is determined on the basis of the geometric data of the component to be sprayed. Here, spraying specifications are usually taken into account, which may, for example, contain specifications regarding the lateral distance between adjacent spraying paths and regarding the lateral overlap of adjacent spraying paths.

[0085] In a further step S3, suitable spray pattern data (brush curve) is determined in a simulation, the spray pattern data representing the spray thickness distribution which results in an acceptable spraying result in the simulation. For example, Figure 3 shows the spray thickness distribution of a rotary atomizer, where there are a plurality of spray pattern data describing the spray thickness distribution. The most important value describing the spray thickness distribution here is the SB50 value, which reflects the width of the spray thickness distribution within which the spray thickness is at least 50% of the maximum spray thickness SD MAX of. The simulation of step S3 will be described in detail later with reference to Figure 2 in detail.

[0086] Then, in step S4, the acceptable spray pattern data determined in the simulation is stored in a first data set.

[0087] In a further step S5, additional spraying data is determined, such as the required spray thickness, spraying type, application device type, coating type (primer / varnish), path speed of the application device and application efficiency. Then, in step S6, this spraying data is stored together with the spray pattern data in the first data set.

[0088] In step S7, then a specific spraying characteristic map is provided by the manufacturer in order to determine relevant application parameters from the suitable spray pattern data, which actually results in the implementation of the suitable spray pattern data.

[0089] In the next step S8, the characteristic map is then used to determine suitable application parameters from the suitable spray pattern data and the spraying data. For example, the application parameters may include the shaping air flow, high voltage charging and paint flow rate of the rotary atomizer.

[0090] Then, in step S9, the suitable application parameters are stored in a second data set.

[0091] In the next step S10, the spraying device will operate with the specified robot path data and the determined application parameters. In the case of an optimized calculated characteristic map, operating the spraying device with the application parameters read out from the characteristic map results in the spray pattern data previously determined in the simulation, so that a good match can be achieved between the simulation and the actual spraying operation.

[0092] It should be mentioned here that the above programming method can determine the spray pattern data and the associated application parameters separately for different path segments of the robot path. This means that the application parameters do not have to remain constant along the robot path. Instead, in order to achieve good spraying results, the application parameters can vary along the robot path.

[0093] In the following, the simulation according to Figure 1A step S3 in Figure 2 will be described in more detail with reference to

[0094] In the first step S3.1 of the simulation, a default value for the spray pattern size is first specified, which can also be referred to as a reference brush. Subsequently, the spraying result is simulated based on the specified default value.

[0095] In the second optimization step S3.2, the uniformity of the spray thickness is then tested at the simple module joints between two adjacent modules. In the context of the present invention, the term simple module joint refers to the boundary between exactly two adjacent spray modules. For example, the boundary between the front door and the rear door forms such a simple module joint. Then, the robot path is optimized in the context of the simulation until the maximum improvement in the spray thickness uniformity at the simple module joints is achieved. Therefore, the second optimization step S3.2 can include a plurality of iterative loops that are run one after another. Importantly, the spray thickness uniformity at the simple module joints is evaluated and used to optimize the robot path.

[0096] In the third optimization step S3.3, the layer thickness uniformity at the complex module joints between more than two adjacent spray modules can be checked. The term complex module joint refers to the boundary between more than two adjacent spray modules. For example, the boundary between the fender, the hood, the front door, and the A-pillar of a motor vehicle body constitutes such a complex module joint. In the third optimization step S3.3, the robot path is again repeatedly optimized until the maximum improvement in the layer thickness uniformity at the complex module joints is achieved.

[0097] In the fourth optimization step S3.4, the layer thickness uniformity at the complex and / or simple module joints is determined again and used as an optimization criterion. However, it is not the robot path that is optimized, but the spray pattern data (brush curve), until the maximum improvement in the layer thickness uniformity at the simple or complex module joints is achieved.

[0098] In the fifth optimization step S3.5, the spray thickness uniformity at the edges of the component is checked and used as an optimization criterion. For example, the spray thickness uniformity at the edges of the engine hood can be checked and taken into account. During the optimization process, the spray pattern data and / or the robot path can be optimized until the maximum improvement in layer thickness uniformity at the edges of the component is achieved. Here, the optimization can also include multiple iterative cycles, which are run one after another.

[0099] Figure 3 Shows the film thickness distribution typically produced by a rotary atomizer.

[0100] Figure 4 Shows the corresponding film thickness distribution of the rotary atomizer when the paint flow rate changes from 70% to 130%.

[0101] Figure 5 Shows a characteristic diagram which, in the context of the present invention, can be used to determine suitable application parameters from the spray pattern data. In Figure 5 the characteristic diagram shown, the spray pattern data is the SB50 value, and the application parameters are the air flow rate and the paint flow velocity. However, within the scope of the present invention, multi-dimensional characteristic diagrams can also be used, which relate more spray pattern data or application parameters.

[0102] Figure 6 Shows in a highly simplified and themed form a spraying device according to the present invention, which is suitable for performing the programming method according to the present invention.

[0103] Thus, the spraying device according to the present invention first comprises, in accordance with a known spraying device, a spraying device controller 1 which, during operation, controls a spraying robot and an application device (e.g. a rotary atomizer) having certain application parameters. The spraying device controller 1 receives the robot path data as input variables, which specify the route of the robot path, according to which the robot path data can be specified according to the spraying specification.

[0104] In addition, the spraying device controller 1 receives geometric data which reflect the geometric characteristics of the component to be sprayed.

[0105] Finally, the spraying device controller 1 receives spraying data which reflect, for example, the type of spraying used.

[0106] During the spraying operation, the spraying installation control 1 then controls the spraying robot and the application device accordingly using the application parameters determined by the programming method according to the present invention.

[0107] For this purpose, a simulation tool 2 is provided which also receives the spraying data, the geometric data and the robot path data and determines suitable spray pattern data as part of the simulation, as described above, which results in an acceptable spraying result in the simulation.

[0108] Furthermore, the spraying device has a characteristic map element 3 for determining the application parameters of the spraying device device controller 1, which will be described in detail.

[0109] The spraying device according to the invention also has a data interface 4 for transmitting suitable spraying pattern data and spraying data to the spraying device manufacturer or a service provider commissioned by the latter, and the manufacturer or service provider also has a data interface 5 for this purpose. On the manufacturer's side, the suitable characteristic map represented by the transmitted spraying pattern data and the transmitted spraying data can be read out from the characteristic map memory 6 and transmitted to the spraying device operator, and then the operator stores the suitable characteristic map in the characteristic map element 3. Then, the characteristic map stored in the characteristic map element 3 enables the determination of suitable application parameters from the simulated spraying pattern data.

[0110] Figure 7 A modification of the flowchart according to Figure 1A is shown. To avoid repetition, reference is first made to the above description of Figure 1A the above.

[0111] The particularity of this modification lies in the processing steps S4 and S5, which are inserted into the processing sequence. Therefore, the method according to Figure 1A assumes that the path of the robot is fixed and does not change during the simulation. However, it may happen that for a certain fixed robot path, even the best spraying pattern data (brush curve) cannot lead to an acceptable spraying result. For example, this may occur if the specified robot path is particularly demanding in terms of spraying technology. In this case, it also makes sense to optimize the robot path.

[0112] Therefore, in step S4, after the best spraying pattern data has been determined, a check is made to determine whether the simulated spraying result is acceptable. If so, the process can continue with step S6 as described above with reference to Figure 1A the description.

[0113] On the other hand, if the simulated spraying result is unacceptable even with the best possible spraying pattern data, the robot path is optimized in step S5, and steps S3, S4, and S5 are repeated until the simulation with the best possible spraying pattern data and the optimized robot path results in an acceptable spraying result. If this is the case, it is possible to enter step S6 as described above with reference to Figure 1A already described.

[0114] The present invention is not limited to the above preferred embodiments. On the contrary, a large number of variations and modifications are possible, which also utilize the concepts of the present invention and thus fall within the scope of protection. In particular, the present invention also claims the subject matter and features of the dependent claims, which are independent of the respective claims mentioned, and in particular do not have the features of the main claim. Therefore, the aspects of the present invention are protected independently of each other.

[0115] List of reference numerals

[0116] 1 Spraying equipment controller

[0117] 2 Simulation tool

[0118] 3 Feature map element

[0119] 4 Data interface

[0120] 5 Data interface

[0121] 6 Feature map memory

Claims

1. A method for programming a program-controlled spraying device for spraying a component with a spraying robot and an application device, having the following steps: a) specifying or determining geometric data, which represent the geometric characteristics of the component to be sprayed (S1); b) specifying robot path data (S2); b1) The robot path data define a robot path, which is traversed by the paint landing points of the application device guided by the spraying robot during the spraying operation; and b2) The robot path is defined according to the predetermined geometric data of the component to be sprayed; c) determining suitable spraying pattern data (S3); c1) The spraying pattern data represent a layer thickness distribution, which is generated by the application device on the surface of the component around the paint landing points during the actual spraying operation; and c2) The determined spraying pattern data are determined to achieve an acceptable spraying result when spraying the component along the specified robot path during the actual spraying operation; c3) The suitable spray pattern data is determined by simulation, which takes into account the specified robot path data and the geometric data of the component to be sprayed; c4) The spray pattern data is optimized during the simulation until an acceptable spraying result is simulated, and c5) The suitable spray pattern data is stored in a first data set (S4). It is characterized by including the following steps: d) Determine suitable application parameters for operating the application device (S8); d1) The suitable application parameters are determined from the spray pattern data contained in the first data set according to a characteristic map; d2) During the actual operation of the application device, when the robot path is traversed, the determined suitable application parameters achieve the suitable spray pattern data; and d3) The suitable application parameters are stored in a second data set (S9); and e) Operate the spraying device (S10); e1) Control the spraying robot according to the robot path data so that the paint landing point of the application device traverses a predetermined robot path on the surface of the component to be sprayed; and e2) Control the application device with the suitable application parameters contained in the second set of data.

2. The method according to claim 1, wherein The method is a method for programming a spraying device for spraying a motor vehicle body component with a spraying robot.

3. The method according to claim 1, wherein The layer thickness distribution is a three-dimensional layer thickness distribution.

4. The method according to claim 1, wherein The method has the following steps: a) Check the simulated spraying result after determining the possible spray pattern data; b) If the check shows that the spraying result is unacceptable, optimize the given robot path; c) Repeatedly determine the possible spray pattern data and optimize the robot path until the simulated spraying result can be accepted.

5. The method according to claim 1, wherein a) The determination of the suitable spray pattern data is carried out within the simulation framework of the operator of the spraying device; b) A first data set with the suitable spray pattern data determined during the simulation is transferred from the operator side to the manufacturer side of the spraying device; c) The determination of the suitable application parameters is carried out on the manufacturer side according to the characteristic map and the suitable spray pattern data; and d) A second data set with the suitable application parameters is transferred from the manufacturer side to the operator side.

6. The method according to claim 5, wherein The determination of the suitable spray pattern data is carried out automatically or with the intervention of an assisting user.

7. The method according to claim 5, wherein A first data set with the suitable spray pattern data determined during the simulation is transferred from the operator side to the service provider side.

8. The method according to claim 5, wherein The determination of the suitable application parameters is carried out by the service provider.

9. The method according to any one of claims 1 to 8, characterized in that a) The determination of the suitable spray pattern data is carried out within the simulation framework of the operator of the spraying device; b) The characteristic map for determining the suitable application parameters is created on the manufacturer side; c) The characteristic map for determining the suitable application parameters is transferred from the service provider to the operator side; and d) The determination of the suitable application parameters is carried out on the operator side according to the characteristic map and the suitable spray pattern data.

10. The method according to claim 9, characterized in that, The determination of the suitable spray pattern data is carried out automatically or with the intervention of an assisting user.

11. The method according to claim 9, wherein The characteristic map for determining the suitable application parameters is created by the service provider.

12. The method according to any one of claims 1 to 8, characterized in that, a) The first data set with suitable spray pattern data further contains the following spraying data: a1) The ideal spraying thickness of the coating agent layer on the component surface; a2) A coating agent identifier for identifying the coating agent and / or the properties of the coating agent; a3) An application device identifier for identifying the application device and / or the properties of the application device; a4) Layer information for distinguishing different layers in multi-layer spraying; and / or a5) The path speed of the paint landing point along the robot path; and / or b) When determining suitable application parameters, not only the spray pattern data contained in the first data set but also the spraying data contained in the first data set should be considered.

13. The method according to claim 12, wherein The ideal spraying thickness of the coating agent layer on the component surface is the spraying thickness in the dry state.

14. The method according to claim 12, wherein The layer information is the layer information for distinguishing the primer layer and the clear coat layer.

15. The method according to claim 12, wherein When determining suitable application parameters, a reference value for the path spacing, a reference value for the path speed, the target layer thickness, the solid content of the coating agent, and the application efficiency of the application device as an assumed empirical value should also be considered.

16. The method according to any one of claims 1 to 8, characterized in that The robot path data contains the following data: a) The spatial route of the robot path; and / or b) The path speed of the paint landing point along the robot path; and / or c) The path spacing between laterally adjacent, laterally overlapping, or adjacent path segments in the robot path; and / or d) The arrangement of the application device; and / or e) The time route of the paint landing point along the robot path or the speed of the paint landing point along the robot path; and / or f) The opening point and / or the closing point of the paint flow.

17. The method according to claim 12, characterized in that, The method includes the following steps in the simulation: a) Subdividing the robot path into a plurality of consecutive path segments that will be sequentially traversed by the paint landing points of the application device; b) Determining a suitable spray pattern for each path segment of the robot path; c) Determining a suitable coating agent flow rate for each path segment of the robot path. d) The first data set with suitable spray pattern data contains a suitable spray pattern and a suitable coating agent flow rate for each path segment of the robot path.

18. The method according to claim 17, wherein Determine a suitable coating agent flow rate for each path segment of the robot path in the form of a percentage, a relative value, or a virtual value.

19. The method according to claim 17, wherein The first data set with suitable spray pattern data contains a suitable spray pattern and a suitable coating agent flow rate for each path segment of the robot path in the form of a percentage, a relative value, or a virtual value.

20. The method according to claim 16, wherein The simulation is carried out in the following iterative optimization steps: a) In the first optimization step, default values of the spraying pattern and the coating agent flow rate are specified, and a spraying result is simulated with the default values; and / or b) In the second optimization step, the spraying thickness uniformity at a simple module connection between exactly two adjacent spraying modules on the surface of the component to be sprayed is tested, and the robot path is optimized to improve the spraying thickness uniformity at the simple module connection; and / or c) In the third optimization step, the layer thickness uniformity at a complex module connection between more than two adjacent spraying modules on the surface of the component to be sprayed is tested, and the robot path is optimized to improve the layer thickness uniformity at the complex module connection; and / or d) In the fourth optimization step, the spraying thickness uniformity at a simple and / or complex module connection between adjacent spraying modules on the surface of the component to be sprayed is tested, and the following variables are optimized to improve the spraying thickness uniformity at the simple and / or complex module connection: d1) Spraying pattern data; and / or d2) Coating agent flow rate; and / or e) In the fifth optimization step, the spraying thickness uniformity at the edge of the component to be sprayed is tested, and the following variables are optimized to improve the spraying thickness uniformity at the edge of the component: e1) Robot path; e2) Spraying pattern data; and / or e3) Coating agent flow rate.

21. The method according to claim 20, wherein, In the first optimization step, default values of the spraying pattern and the coating agent flow rate are specified in the form of percentages, relative values or virtual values.

22. The method according to claim 20, wherein In the second optimization step, the robot path is optimized to improve the spraying thickness uniformity between the fender and the hood, between the front door and the rear door, and between the modules on the roof of the motor vehicle.

23. The method according to claim 20, characterized in that, In the third optimization step, the robot path is optimized to improve the layer thickness uniformity at the junction of the fender, the hood, the front door, the A-pillar or the rear fender and the rear pillar.

24. The method according to claim 17, wherein The default values in the first optimization step of the simulation are specified according to the following variables: a) A reference value of the path distance between the central axes of directly adjacent spraying paths; b) The overlap of directly adjacent spraying paths; and / or c) A reference value of the coating agent flow rate.

25. The method according to any one of claims 1 to 8, characterized in that The simulated spraying result is graphically represented on the operator's screen.

26. The method according to claim 25, wherein The simulated spraying result is represented on the operator's screen with a perspective representation of the component to be sprayed as a model, and the surface positions of the model are represented by colors according to the simulated local spraying thickness.

27. The method according to claim 25, characterized in that, The simulated spraying result is represented on the operator's screen with colors representing the surface positions of the model corresponding to the deviation between the simulated local spraying thickness and a predetermined reference value of the spraying thickness.

28. The method according to any one of claims 1 to 8, characterized in that, A characteristic diagram for determining suitable application parameters related to a specific coating agent and / or the spraying device used relates the following variables to each other: a) The width of the spraying thickness distribution; b) The shaping air flow of the application device; c) The coating agent flow rate of the application device; d) The rotational speed of a rotary atomizer used as the application device; e) The high voltage of the electrostatic coating agent charge; f) The path speed of the application device along the robot path; g) The spraying distance between the application device and the surface of the component to be sprayed.

29. The method according to claim 28, wherein The width of the spraying thickness distribution is the SB50 value of the spraying thickness distribution.

30. The method according to any one of claims 1 to 8, characterized in that, a) The robot path data is specified by the operator of the spraying device on the operator side; and / or b) The geometric data of the component to be sprayed is specified by the operator of the spraying device on the operator side.

31. The method according to claim 30, wherein The robot path data is specified on the operator side automatically or with the intervention of the user assisting.

32. The method according to claim 30, wherein The geometric data of the component to be sprayed is specified on the operator side automatically or with the intervention of the user assisting.

33. A spraying device for a spraying component, having a) at least one spraying robot; b) at least one application device guided by the spraying robot; and c) a controller for controlling the application device and the spraying robot, characterized in that, d) The controller executes the method according to any one of claims 1 to 32.

34. The spraying device according to claim 33, characterized in that, The spraying device is used for spraying motor vehicle body components.

35. The spraying device according to claim 33, characterized in that, The characteristic map is stored in the controller in order to determine suitable application parameters from suitable spraying pattern data.

36. The spraying device according to any one of claims 33 to 35, characterized in that, The spraying device has a data interface for transmitting a first data set with suitable spraying pattern data to a service provider and for receiving a second data set with suitable application parameters from the service provider.

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