Coating thickness optimization and programming method for a coating system and corresponding coating system

Patent metadata

Field	Value
Publication number	US-11819862-B2
Application number	US-202017609431-A
Country	US
Kind code	B2
Filing date	May 8, 2020
Priority date	May 20, 2019
Publication date	Nov 21, 2023
Grant date	Nov 21, 2023

Abstract

The disclosure relates to a method for programming a program-controlled coating robot for coating components. A robot path is preset and application parameters observed by the applicator are also preset based on real coating operation during movement along the robot path. There is a virtual determination of a coating result for the predetermined robot path and the predetermined application parameters. The disclosure provides steps for virtual determination of the coating result including generating real spray pattern data and/or reading out real spray pattern data from a database as a function of the predetermined robot path and/or the predetermined application parameters, the read-out real spray pattern data reproducing a spray pattern which the applicator generates during a real coating operation with the predetermined application parameters and/or on the predetermined robot path, and determining the coating result taking into account the real spray pattern data read out from the database or the generated spray pattern data.

First claim

The invention claimed is:

1. A method for programming a program-controlled coating robot for coating components, comprising:
a) specifying a robot path which is to be traversed by a paint impact point of an applicator guided by the coating robot in coating operation,
b) specifying application parameters which are to be maintained by the applicator and the coating robot in real coating operation during movement along the robot path, the application parameters include a surface brush set of parameters and an edge brush set of parameters, the surface brush set of parameters having a wider coating thickness profile than the edge bush set of parameters,
c) virtually determining a coating result for the predetermined robot path and the predetermined application parameters, wherein virtually determining the coating result includes:
c1) generating, or reading out from a database, real spray pattern data as a function of the predetermined robot path, the surface brush set of parameters, and the edge brush set of parameters, the real spray pattern data generated or read out from the database reproducing a spray pattern which the applicator generates during a real coating operation with at least one of the predetermined application parameters and on the predetermined robot path, and
c2) determining the coating result taking into account the real spray pattern data generated or read out from the database.

2. A method according to claim 1 , further comprising:
optimizing the robot path and the application parameters as a function of the determined virtual coating result.

3. A method according to claim 1 , wherein determining the spray pattern data further comprises:
a) carrying out real application trials with different application parameters and different robot paths,
b) measuring the spray pattern during the real application tests and determining the corresponding spray pattern data for the different application parameters and robot paths, and
c) storing the spray pattern data for the various application parameters and robot paths in the database.

4. A method according to claim 3 , wherein the real application trials are made by coating trial sheets with the different application parameters.

5. A method according to claim 3 , wherein
a) the spray pattern data are partly determined in the real application tests and are based on the measurement of the spray patterns, and
b) the spray pattern data are partially interpolated from the spray pattern data determined in the real application tests and based on the measurement of the spray patterns.

6. A method according to claim 1 , wherein
the database contains the surface brush set of parameters and the edge brush set of parameters.

7. A method according to claim 6 , wherein
the database contains spray pattern data for variations of the edge brush set of parameters.

8. A method according to claim 1 ,
further comprising the following steps:
a) determining coating results for different variations of the surface brush set of parameters; and
b) selecting one variation of the different variations of the surface brush set of parameters based on the determined coating results.

9. A method according to claim 1 ,
further comprising:
a) virtually determining coating results for different variations of the edge brush set of parameters, and
b) selecting one variation of the different variations of the edge brush set of parameters based on the determined coating results.

10. A method according to claim 1 ,
further comprising:
a) virtually determining coating results for different variations of the robot path; and
b) selecting one variation of the different variations of the robot path based on the determined coating results.

11. A method according to claim 1 , wherein the real spray pattern data generated or read out from the database as a function of the predetermined robot path, the surface brush set of parameters, and the edge brush set of parameters includes a coating thickness profile.

12. A method according to claim 11 , wherein the real spray pattern data generated or read out real spray pattern data from the database as a function of the predetermined robot path, the surface brush set of parameters, and the edge brush set of parameters includes an SB value and an SDmax-value of the coating thickness profile.

13. A method according to claim 1 , wherein
a) the spray pattern data reproduce a coating thickness profile, and
b) the coating thickness profile is represented by mathematical curves.

14. A method according to claim 13 , wherein the mathematical curves are Gaussian curves.

15. A method according to claim 1 , wherein
a) the coating result is represented graphically with a coating thickness distribution, and
b) the coating result is calculated taking into account the read-out spray pattern data and the application parameters.

16. A method according to claim 1 , wherein the application parameters determine at least one of the following operating variables of the applicator and the coating robot:
a) atomizer rotational speed of a rotary atomizer forming the applicator,
b) shaping air flow or shaping air pressure of shaping air delivered to form a spray of the applicator,
c) high voltage of an electrostatic coating agent charge, or
d) drive air flow or drive air pressure for driving a compressed air turbine of a rotation atomizer forming the applicator.

Assignees

• Duerr Systems Ag

Inventors

• Nolte Hans-Jürgen
• Herre Frank
• Heckeler Christoph

Classifications

• B05B13/0431

  with spray heads moved by robots or articulated arms, e.g. for applying liquid or other fluent material to three-dimensional [3D] surfaces · CPC title

• B05B12/084 Primary

  responsive to condition of liquid or other fluent material already sprayed on the target, e.g. coating thickness, weight or pattern · CPC title

• B25J9/1664 Primary

  characterised by motion, path, trajectory planning · CPC title

• G06F30/20

  Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30) · CPC title

• B05B12/00

  Arrangements for controlling delivery; Arrangements for controlling the spray area · CPC title