Granted Patent B2

US 12,541,194 · App. 17/608,470 · Granted Feb 3, 2026

Inventors: Simon Alt (Ditzingen, DE); Jan-Philipp Schuh (Lauffen a.N., DE); Ralf Schurer (Marbach am Neckar, DE); Markus Hummel (Urbach, DE); Jens Berner (Möglingen, DE); Jens Häcker (Markgröningen, DE); Thomas Hezel (Asperg, DE); Frank Herre (Oberriexingen, DE); Michael Zabel (Winnenden, DE); Dietmar Wieland (Waiblingen, DE); Philipp Oetinger (Sachsenheim, DE); Robin Heim (Güglingen, DE)

Assignee: Dürr Systems AG

G05B19/41875G05B2219/32368

Abstract

Claims (33)

1 . A method for analyzing surface imperfections of workpieces, preferably of vehicle bodies and/or vehicle attachment parts, in particular after and/or whilst passing through a production process in industrial-method plants, preferably after and/or whilst passing through a painting process in painting plants, the method comprising:

creating a workpiece-specific data set, uniquely assigned to a workpiece, at a start of a production process, in particular at the start of a painting process, and/or creating a workpiece-carrier-specific data set, uniquely assigned to a workpiece carrier, at the start of a production process, in particular at the start of a painting process;

supplementing the workpiece-specific data set while a workpiece is passing through the production process, in particular the painting process, with in particular quality-relevant process data and/or supplementing the workpiece-carrier-specific data set while a workpiece carrier is passing through the production process, in particular the painting process, with in particular quality-relevant process data; and

storing the workpiece-specific data set in a database and/or storing the workpiece-carrier-specific data set in a database,

wherein the workpiece-specific data set and/or the workpiece-carrier-specific data set is supplemented with quality data that contains information about surface imperfections of the particular workpiece, preferably at an end of the production process, in particular at the end of the painting process,

wherein quality data from a plurality of workpiece-specific data sets and/or from a plurality of workpiece-carrier-specific data sets are automatically classified into different quality deficiency clusters by a cluster method for the detection of systematic surface imperfections, and

wherein workpieces are ejected from the production process based on the quality deficiency clusters detected by the cluster method.

2 . The method in accordance with claim 1 , wherein, by an analysis procedure, quality deficiency causes for the systematic surface imperfections detected by the cluster method and classified into different quality deficiency clusters are automatically determined, preferably by analysis of the in particular quality-relevant process data of the workpiece-specific data sets of the workpieces with systematic surface imperfections of a particular quality deficiency cluster and/or by analysis of the in particular quality-relevant process data of the workpiece-carrier-specific data sets of the workpiece carriers for which the workpieces have systematic surface imperfections of a particular quality deficiency cluster.

3 . The method in accordance with claim 2 , wherein the determined quality deficiency causes include anomalies and/or deviations in the production process, in particular in the painting process.

4 . The method in accordance with claim 2 , wherein correlations between the determined quality deficiency causes and the systematic surface imperfections classified into different quality deficiency clusters are determined by the analysis procedure.

5 . The method in accordance with claim 4 , wherein imminent systematic surface imperfections are automatically determined by the determined correlations, preferably by automatically inferring future surface imperfections of a workpiece from one or more anomalies and/or deviations determined in the ongoing production process by the correlations determined by the analysis procedure, while a workpiece is passing through the production process.

6 . The method in accordance with claim 1 , wherein the workpiece-specific data set and/or the workpiece-carrier-specific data set is supplemented in each individual process step with, in particular, quality-relevant process data.

7 . The method in accordance with claim 1 , wherein one or more of the following process parameters are used as in particular quality-relevant process data, by which a workpiece-specific data set and/or a workpiece-carrier-specific data set is supplemented:

target-time overruns in process steps of the production process;

events occurring during a run-through of a process step of the production process;

body-in-white quality data of a particular workpiece;

anomalies and/or deviations in the production process;

weather data; and

personal data for persons who were involved in a process step of the production process when it was run through.

8 . The method in accordance with claim 1 , wherein the workpiece-specific data set and/or the workpiece-specific data set is supplemented with process fault data containing information about an anomaly and/or deviation in a process step of the production process whilst a workpiece and/or a workpiece carrier passes through the process step of the production process.

9 . The method in accordance with claim 1 , wherein the method is performed in an industrial-method plant, in particular in a painting plant, which includes a plurality of treatment stations which are different from one another and in each of which one or more process steps of the production process, in particular of the painting process, can be performed.

10 . The method in accordance with claim 1 , wherein the workpiece-specific data set and/or the workpiece-carrier-specific data set is supplemented continuously or discontinuously with the in particular quality-relevant process data.

11 . The method in accordance with claim 1 , wherein the workpiece-specific data set and/or the workpiece-carrier-specific data set is supplemented in each case with in particular quality-relevant process data which in each case include a time stamp by which the particular process data can be uniquely assigned to a time and/or a process step of the production process.

12 . The method in accordance with claim 1 , wherein the supplemented workpiece-specific data set of a workpiece and/or the supplemented workpiece-carrier-specific data set of a workpiece carrier is stored in a database during and/or after the passing of a workpiece and/or a workpiece carrier through the production process.

13 . A quality analysis system for analyzing surface imperfections of workpieces, preferably of vehicle bodies, in particular after and/or whilst passing through a production process in industrial-method plants, preferably after and/or whilst passing through a painting process in painting plants, comprising

an interface for communication with a control system of an industrial-method plant, in particular a painting plant; and

a control device which is set up and configured in such a way that the method in accordance with claim 1 can be carried out by the control device.

14 . An industrial-method plant, in particular a painting plant, comprising:

one or more treatment stations;

a control system by which a production process, in particular a painting process, in the one or more treatment stations can be controlled; and

a quality analysis system in accordance with claim 13 .

15 . The method in accordance with claim 1 , wherein the systemic surface imperfections detected by the cluster method are displayed to a user via a visualization.

16 . The method in accordance with claim 1 , wherein a process control system of the production process is adapted on a basis of quality deficiency clusters detected by the cluster method.

Priority Claims (2)

Continuity (1)

References Cited (215)