US 12,275,034 B2
Coating production line system
Marlon Boldrini, Zürich (CH)
Assigned to coatingAI AG, Winterthur (CH)
Filed by coatingAI AG, Winterthur (CH)
Filed on Dec. 6, 2022, as Appl. No. 18/062,242.
Claims priority of application No. 21212625 (EP), filed on Dec. 6, 2021.
Prior Publication US 2023/0173533 A1, Jun. 8, 2023
Int. Cl. B05C 11/10 (2006.01); B05C 19/00 (2006.01); B05D 7/24 (2006.01)
CPC B05C 11/1021 (2013.01) [B05C 19/008 (2013.01); B05D 7/24 (2013.01); B05D 2401/32 (2013.01)] 11 Claims
OG exemplary drawing
 
1. A coating production line system for coating work pieces comprising:
a coating powder source;
a coating apparatus configured to provide a coating for the work pieces with a coating powder provided by the coating powder source;
an inspection unit configured to measure a thickness of a coating applied to the work pieces;
a conveyor unit configured to move the work pieces through the coating apparatus and the inspection unit in this order;
a control unit in communication with the inspection unit, the coating apparatus and the conveyor unit; and
a database comprising coating parameters and thickness requirement data for the work pieces to be coated as well as a coating powder characteristics parameter, related to a composition of the coating powder used in the coating apparatus and based on one or more of the following five parameters of the coating powder: coloring type, binding material type, surface finish type, binding material versus color pigment ratio and grain size;
wherein the control unit is configured to retrieve thickness requirements and coating parameters from the database, to control the coating apparatus based on said coating parameters, wherein the control unit comprises a machine learning instance;
wherein the control unit is further configured to retrieve from the database the coating powder characteristics parameter as an input vector for the machine learning instance for generating an output vector to control the coating apparatus, wherein the output vector defines at the same time a first additional part vector; and
wherein the control unit is further configured to determine the coating quality based on a comparison between the thickness data acquired from the inspection unit for a coated work piece and the retrieved thickness requirement data as a second additional part vector; and
wherein the control unit is configured to feed back the first additional part vector and the second additional part vector as additional parts to the next input vector for the machine learning instance.